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THE HOUSEHOLD VULNERABILITY INDEX FRAMEWORK

(HVI)

By

Dr L.M Sibanda, T Kureya and U Chipfupa

Vulnerability assessment for better programming

REGIONAL SECRETARIAT 141 Cresswell Road, Weavind Park 0184 Private Bag X813, Silverton 0127 Pretoria, South Africa

Tel: +27 12 845 9100 Fax: +27 12 845 9110 Email: policy@fanrpan.org www.fanrpan.org

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Table of Contents Chapter 1: Conceptual Framework .................................................................................. 4

1.0 Background to the HVI ......................................................................................... 4

1.2 What is the HVI? ................................................................................................... 4

1.3 Why is the HVI important? ................................................................................... 5

1.4 Who are the stakeholders for the HVI? ................................................................. 5

1.5 HVI and Vulnerability ........................................................................................... 6

1.6 The HVI Conceptual framework ........................................................................... 6

Chapter 2: Review of Literature ..................................................................................... 11

2.1 HIV and AIDS, Household Vulnerability and Food Security ............................... 11

2.2 Sustainable Livelihood Framework ...................................................................... 11

2.3 Review of HIV and AIDS Impact on Rural Livelihoods ...................................... 13

2.3.1 Human Capital .............................................................................................. 13

2.3.2 Financial Capital ........................................................................................... 21

2.3.3 Physical Capital ............................................................................................. 28

2.3.4 Natural Capital .............................................................................................. 31

2.3.5 Social Capital ................................................................................................ 32

Chapter 3: Theoretical Framework to HVI Development ............................................. 33

3.1 Approaches to HVI Index Development ............................................................. 34

3.1.1 Principal Component Analysis ...................................................................... 34

3.1.2 Fussy Set Approach to Household Vulnerability Index Analysis ................... 35

3.2 Steps taken in designing HVI Computations ....................................................... 36

Chapter 4: HVI Methodology........................................................................................ 39

4.1 HVI Data Requirements ...................................................................................... 39

4.2 HVI Database ..................................................................................................... 41

4.3 HVI Web Portal .................................................................................................. 41

Chapter 5: Pilot Testing of the HVI .............................................................................. 43

5.1 Pilot Testing of the HVI ...................................................................................... 43

5.2 Issues to be addressed in order to reduce vulnerability ........................................ 45

5.3 Major Findings and Recommendations from Pilot Testing .................................. 46

Chapter 5: Application of the HVI ................................................................................ 48

5.1 Where is the HVI applicable? .............................................................................. 48

5.1.1 Programming and targeting ....................................................................... 48

5.1.2 Vulnerability Assessments ......................................................................... 49

5.1.3 Monitoring and Evaluation ....................................................................... 49

Chapter 6: Reception of the HVI in the SADC Region ................................................. 50

6.1 Introduction of HVI to regional development partners ....................................... 50

6.2 HVI Regional Policy Dialogue Workshop ........................................................... 50

6.3 Use of the HVI by FOSENET and World Vision International .......................... 51

6.4 Other partners in the SADC region that would find the HVI useful .................... 52

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Chapter 1: Conceptual Framework

1.0 Background to the HVI

The HIV pandemic has increased the challenge for attaining sustainable development in

Southern Africa. There has been a marked decline in quality of life, especially for poor and

marginalized populations, while virtually all sectors of society have been affected by the

pandemic. According to Save the Children, 2002, the pandemic is threatening the lives of some

16 million people in the region. UNAIDS (2002) reports that of the 25.3 million infected people

with HIV in the world, 70% of the total are in sub-Saharan Africa. The report also states that of

the entire infected population of adults in Africa, 20% came from only eight southern African

countries – Botswana, Lesotho, Mozambique, Namibia, South Africa, Swaziland, Zambia and

Zimbabwe. Such a situation in the region is alarming and has called for greater efforts in

understanding how the pandemic affects the livelihoods of the African communities and hence

inform policy on actions that need to be taken to reverse the impact on society especially with

specific reference to agriculture and food security. Given this background the Food, Agriculture

and Natural Resources Policy Analysis Network (FANRPAN) in collaboration with Southern

Africa Development Community (SADC) and European Union (EU) undertook a seven country

study in 2004 whose main objective was to assess the impact of HIV and AIDS on agriculture

and food security. One of the key outcomes of this study was to develop and test a statistical

index that attempts to quantify vulnerability introduced into different households by HIV and

AIDS. The index would provide a baseline on how to quantify the different degrees of

vulnerability experienced by different households. This gave birth to the concept of the HVI.

1.2 What is the HVI?

The Household Vulnerability Index (HVI) is a measure that was developed by the Food,

Agriculture and Policy Analysis Network (FANRPAN) to measure vulnerability of households

and communities to the impacts of diseases and shocks such as HIV and AIDS and poverty.

HVI achieves this by comparing wealth or assets that are available to a household, and classifies

the households according to three levels of vulnerability to the particular issue. As indicated by

Thomas (2003), to be able to address vulnerability effectively it needs to be measured so that

areas of highest priority can be identified. This equity approach to vulnerability is critical for

sustainable development in general.

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The HVI assesses a household’s access to (1) natural assets such as land, soil and water; (2)

physical assets such as livestock and equipment; (3) financial assets such as savings, salaries,

remittances or pensions; (4) human capital assets such as farm labour, gender composition and

dependents; and (5) social assets such as information, community support, extended families and

formal or informal social welfare support. More that 15 variables (called dimensions) are assessed

together, and a statistical score is calculated for each household. The result, the HVI, is used to

classify a household as either coping (i.e. the household is in a vulnerable situation but still able to

cope) or acute (i.e. the household has been hit so hard that it badly needs assistance to the degree

of an acute health care unit in a hospital) or emergency (i.e. the household has a situation equivalent

to an intensive care situation – almost a point of no return – but could be resuscitated only with

the best possible expertise). Based on these different vulnerability levels specific relief or

development packages are recommended to policy makers for assisting the affected households

overcome their vulnerability.

The HVI provide answers to two most important questions:

1. How can the ‘most vulnerable’ be identified and assisted?

2. How can the impact of the epidemic on household food security be monitored and

evaluated over time?

The HVI provides a yardstick to answer these questions, and when longitudinal data is available,

the HVI will also keep track of progress towards food security in the region.

1.3 Why is the HVI important?

The HVI is important for various reasons. In development work, at last we have a measure that

can compare how different households are fairing given a particular issue. This is critical. Not

only are we able to tell who is most affected, but we not do this objectively, and we even know

the source of their vulnerability. We are thus able to calculate how much is required to move that

household from its situation to a desired level. The reverse is also true. If we have limited

resources, it is possible to know how much our efforts will yield.

The HVI is not an imported tool. It is home-grown, and endeavours to unpack the complexities

that characterize the African way of life, thereby exposing what was not possible to quantify

before. Having said that, it is important to note that like all other tools, the value can be derived

if the tool is applied appropriately.

1.4 Who are the stakeholders for the HVI?

FANRPAN believes the following to constitute stakeholders who will use or have an interest in

the HVI.

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Policy analysts and policy makers

Vulnerability Assessment Committees

Early warning systems

Relief Agencies

HIV and AIDS organisations

Development Organisations

Civil Society Organisations (CSOs)

1.5 HVI and Vulnerability

Before discussing in detail the conceptual framework of the HVI, we need to be very clear on

how vulnerability is defined in the model. The HVI approach conceptualizes vulnerability as the

presence of factors that place households at risk of becoming food insecure or malnourished.

The factors also affect household ability to cope. Vulnerability is described as having two

components: “external vulnerability”, which refers to exposure to external shocks or hazards;

and “internal vulnerability”, which refers to the capacity to cope with or withstand those shocks

(resilience). Household vulnerability is the extent to which HIV and AIDS and other factors

affect a household’s food security status and asset endowments, and the household’s ability or

inability to withstand the shock caused by these factors. All of these factors determine the

livelihood strategies that people pursue, and ultimately their livelihood outcomes.

1.6 The HVI Conceptual framework

The development of the HVI adopted the sustainable livelihoods framework in analyzing how

households are affected by HIV and AIDS and their ability to cope with such shocks. A

livelihood is sustainable when it can cope with and recover from stresses and shocks and

maintains or enhances its capabilities and assets, while not undermining the natural resource base.

Thus the more assets a household has, the lesser its vulnerability. A household livelihood

generally has five assets, that is, human, physical, financial, social and natural capitals. Household

vulnerability evolves from the impact of HIV and AIDS impacts on one or all of these assets. Fig

1 shows the five livelihood assets and how they are affected by HIV and AIDS. These assets are

discussed below:

Human capital- HIV and AIDS impacts on household demographic structure i.e.,

size and composition, and the mobility of household members.

Natural capital- Household vulnerability increases environmental degradation and

access to natural capital.

Physical capital- This includes changes in household physical assets, access to

extension services and changes in optimal farm household production.

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Financial capital- HIV and AIDS evoke changes in household financial assets,

investment choices, household income and expenditure and market access.

Social capital- The pandemic affects family social networks in terms of support, and

inter and intra-relationships from government, community and other relatives.

Household exposure to HIV and AIDS is manifested in a number of ways including decline in

agricultural productivity, reduction in participation in the market, reduction in number and

quality of livestock, increased mobility of household members, increased environmental

degradation, decline in household food consumption, erosion of household productive asset

base, breaking down of social support networks, reduced household investments, increase in

dependency ratios and uncertain access to behavioral change information, inter alia.

Fig 1 Conceptualizing Household Vulnerability to Impact of HIV and AIDS

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As such the ability of HIV and AIDS affected households to cope with the above specified

impacts, which is the capacity to physically survive the shock with their livelihood more or less

intact, greatly depends on their asset ownership as defined by Moser (1998). These assets are as

follows: labour (valuable asset possessed by most poor people), human capital (e.g. education,

skills, and health that determine the ability to emerge from poverty and make enhanced use of

the labour), productive assets (e.g. land and housing, and tools for production), and household

relations (that determine equitable distribution of resources within a family e.g. ensuring that

women have equitable access to food and education) and social capital (relationship between

households and within communities based on kinship, religion, and mutual interdependence).

Financial

Capital

Natural

Capital

Impact of HIV

and AIDS on

Agriculture and

Food Security

(Household Level)

Human

Capital

Changes in household demographic structure -dependency ratio -number of sick members

-household size

Gender implications -female headed hhlds -child headed hhlds

Mobility of household members

- household disintegration due to sickness and/or death

Environmental degradation

-use of forest products -household access to water resources

Changes in household natural capital

base - access to land - % land utilization

Social

Capital

Social Networks -type and $ value of support from government, community and NGOs

Access to behavioral change information

-sources and quality of information on HIV and AIDS and Agriculture

Physical

Capital

Changes in household physical assets -livestock index

-number of farm implements

Changes in optimal farm-hhld production decisions -% cash cropping

-changes in fertilizer application rates

Agricultural extension services

-absenteeism due to illness -access to extension services

Changes in household income and expenditure patterns

- % expenditure of health care - % expenditure on food

Changes in household food and nutrition security

-no. of food safety nets -nutrition diversity index

-total household income

Impact of household market access -net revenue from asset transactions

-crop marketing

Changes in household financial assets - amount of savings (withdrawals, deposits)

- amount of credit loans received

Changes in household investment choices

-farm equipment purchases/sales -livestock purchases/sales

-land purchases/improvements

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Depending on the asset ownership and the subsequent coping strategies adopted by households

to reverse the HIV and AIDS impacts, vulnerability of different households is expected to differ

i.e., households fall into any of the three levels of vulnerability (Fig 2).

Fig 1. Relationship of HIV/AIDS and Rural Household Vulnerability

Household

Exposure to

HIV & AIDS

Ability

to Cope

Level of Household

Vulnerability

1. Coping level households 2. Acute level households 3. Emergency level households

Assets Ownership

1. Labour

2. Human capital

3. Productive assets

4. Household relations

5. Social Capital

Fig 2 Relationship between Impact of HIV and AIDS and Household Vulnerability

Adapted from WFP (VAM) (http://www.wfp.it/vam_documents/va/va99/html) and Moser (1998)

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Hypothetical Example of HVI Application

Given an example of three households that is household A, B and C.

Household A is

Headed by an 18 year old child who is uneducated and no longer attends school

He takes care of 5 brothers and sisters who are going to school

They own 3 cattle

The mother is alive but has relocated back to her kin group because of sickness

They are currently getting support from NGOs in terms of food, seed packs, etc

And on average they harvest 80 kg of maize per season.

Household B is

Headed by a single parent – a woman who has never been married

she has three kids all of whom are going to school

She owns 5 cattle

She is involved in informal work such as gardening

The household harvest an average of 120 kg of maize per season

And she is the sole income earner.

Household C

Has both parents available

The father is bed-ridden

they own no cattle

They have 4 kids who do not go to school

They are involved in casual work

They practice dry tillage And harvest an average of 40 kgs of maize per season. The question is which one of the three families is most vulnerable and which one is least vulnerable and why? Given the information in the example, the HVI would rank

Household C as the highest in terms of vulnerability despite the fact both parents are alive. This is because the household

o does not own any productive assets o they have limited labour available for off farm work o they have low agricultural productivity o they have low literacy levels and hence bleak future

Household B will be ranked the least vulnerable despite the fact that it is headed by a single mother The household

o can afford to send children to school o owns cattle a very important livestock in agric production o has a diversified income source o has labour vital for farm and off farm work

The human, financial and physical capital indices in the HVI model will also show that any meaningful intervention to assist Household C will focus on three issues that is:

o labour saving technologies o livestock projects to replenish household assets

Income generating projects to improve household income

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Chapter 2: Review of Literature

When the HVI was initially developed it was designed to quantify vulnerability introduced by HIV and AIDS on household livelihood. It was at a later stage that it was also discovered that the same model could apply to other vulnerability shocks as they all affect the household livelihood in a similar manner. However literature that is discussed in this section relates to HIV and AIDS and its impact on household livelihoods. This literature was used to inform HVI development and design.

2.1 HIV and AIDS, Household Vulnerability and Food Security

HIV and AIDS affect rural households, most of whom depend on agriculture as a source of

livelihood (Mano and Chipfupa, 2005). Mutangadura et al (1999) and Shapouri and Rosen (2001)

state that HIV and AIDS is a major threat to agriculture and food security because it reduces

agricultural productivity and diminishes the availability of food through direct loss of family

labour, reduction in time allocated to farming, sale of farm assets, cultivation of marginal land

and marginalization of surviving widows from land ownership by customary land tenure systems.

HIV and AIDS cause spending to rise particularly on medical care and funeral expenses (Bates et

al, 2004). FANRPAN’s study on Impact of HIV and AIDS on Agriculture and Food Security also

confirmed the above findings, and generally showed that food production and income declines in

HIV and AIDS affected households. The pandemic exposes rural households to poverty mainly

through its effects on agricultural production and food security.

The extent of this exposure that ics how households are vulnerable to the impacts of HIV and

AIDS depends on their socio-economic and political status. Households are bound to have

varying degrees of resilience and ability to cope and this has implications on the policy

recommendations intended to mitigate the impact of the condition. As refuted by Bates et al

(2004), vulnerability is too broad a concept to enable effective targeting of the most vulnerable

especially when resources are scarce. In their guidelines for vulnerability mapping the World

Food Programme (WFP) (1999) stressed the need for creating a vulnerability database that is

useful to identify both chronic and transitory vulnerabilities that is, groups that are permanently

vulnerable and those that are temporarily vulnerable must be differentiated for appropriate policy

action. This cements the need to develop an appropriate method of quantifying the levels of

vulnerability of each household.

2.2 Sustainable Livelihood Framework

The impact that HIV and AIDS have on rural livelihoods is better explored using the Sustainable

Livelihoods (SL) framework approach. According to the SL framework, households are only

viewed as being sustainable if they can adjust to threats without compromising their future ability

to survive shocks to their livelihoods and HIV and AIDS is potentially one of those shocks

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(Carney, 1998). The most common hypothesis that relates the impact of HIV and AIDS on asset

accumulation and holding capacity of rural households is that the pandemic strips individuals,

households, networks and communities of assets (Gillespie and Haddad, 2001). The pandemic is

alluded to represents a potentially devastating shock to farm household survival. The illness or

death of one or more household members can affect each of the livelihood assets resulting in a

reduction in the ability of the household to adjust to future shocks (Stokes, 2003).

The SL framework (Carney 1998, DFID/FAO, 2000) has provided quite a clear basis for

understanding how HIV and AIDS can impact on various aspects of livelihoods in many

different ways. The framework depicts livelihoods as being determined in the first instance by the

range of assets available to the household. “Assets” is used as a broad term, and five categories of

assets or capital are identified which are human, physical, financial, social and natural capital.

O’Donnell (2004) has argued recently that the SL framework can provide a clear basis for

understanding how HIV and AIDS can impact on various aspects of livelihoods in many

different ways. When considering livelihoods from the perspective of HIV and AIDS, a

livelihood system analysis will take on an additional character. The analysis begins with

identifying livelihood strategies that are susceptible to HIV and AIDS, and then tracks the impact

of AIDS on livelihood assets—human, natural, financial, physical and social. Such an analysis

should reveal intervention points for reducing the risk of HIV infection and mitigating the

negative impact of HIV and AIDS, so that preventive measures can be linked to mitigation

efforts to address both the causes and symptoms of the disease (Tango International, 2003: 4-5).

Drawing on the work of Chambers and Conway (1992) a livelihood is defined as comprising ‘the

capabilities, assets and activities required for a means of living’ (Carney, 1998) As an approach to

understanding and facilitating development the SL approach contains echoes of the basic needs

approach and its evolution into concerns with food security and then poverty alleviation and

reduction (Maxwell, 1998). It also draws on the insights from integrated rural development,

farming systems research and participatory approaches in development. These various strands are

linked with appreciation first of the diversity of livelihoods of rural people, second of the roles of

different types of assets in rural peoples’ livelihoods, and third of the importance of the wider

social and political and economic environment in mediating access to assets. While increasing

evidence has accumulated that rural people engage in many different types of income generating

and livelihood activity (Taylor et al. (2000), Ellis (1998)), it is also recognized that their ability to

engage in non agricultural activities is often very dependent on their access to assets ((Reardon,

1997; Baker ,1995 and El Bashir, 1997, cited by Tacoli 1998); Dercon and Krishna (1996), de

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Janvry and Sadoulet (1996)). These authors show that different types of activities require

different combinations of financial, human, social, physical and natural capital.

As Moser (1998) argues, analysis of the linkages between people’s access to assets and livelihood

diversification goes back into the literature of the late 1980’s on people’s coping strategies in

response to seasonality and famine (Corbett 1989; Davies 1989) and on the role of entitlements

and assets in these coping strategies (Sen 1981; Swift 1989). These coping strategies aim to

maintain a minimum level of consumption by:

Contributing to overall production and income

Allowing exchange and or consumption in periods when there is no income.

Hence analysis of assets in rural livelihoods therefore needs to examine the functions of different

asset types within the asset portfolios held by poor people with different livelihood strategies.

Such analysis must then progress beyond categorization of the type of capital as emphasized by

the SL framework, to identify priorities for policy and for other interventions supporting

expanded access to assets

2.3 Review of HIV and AIDS Impact on Rural Livelihoods

2.3.1 Human Capital

(a) Changes in household demographic structure and labour availability

Human capital assets represent the skills, knowledge, ability to labour and good health that

together enable people to pursue different livelihood strategies and achieve their livelihood

objectives. Smallholder agriculture is labour intensive due to low levels of mechanization. HIV

and AIDS has the potential to erode the active labour force in farming systems where women

and children already make up a higher proportion. HIV and AIDS is debilitating, and reduces

hours at work due to chronic illness. Attending funerals and other related rituals like memorial

services frequently reduces labour time input, which is important to animal well-being and crop

security.

The loss of adult on- and off-farm labour is one of the most widely discussed effects of the HIV

and AIDS pandemic (Topouzis and du Guerny 1999). The loss of experienced agricultural

workers affects both individual households and communities, resulting in labour shortages and

declines in productivity both on and off the farm. Declining productivity, in turn, leads to

declines in household income through both decreases in the household's own production and

through declines in off-farm income and remittances. An increase in household expenditures on

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medical care results in a decline in savings and the loss of assets through the sale of both

productive and non-productive assets. Thus, the loss of human capital leads directly to declines

in the financial capital of the household. For food insecure households or those slightly above

this threshold, the loss of labour, income and increased expenditures for medical care can push

them further into poverty and food insecurity (Stokes, 2003). In Tanzania studies reveal that, by

2010, the estimated size of the labour force will shrink by 20 percent because of AIDS, and the

mean age of workers will fall from 32 to 28 due to a shift to younger and less experienced

workers (Jackson, H. 1997).

Committee on World Food Security (2001) estimated that approximately 2-person years of

labour are lost by the time one person dies of AIDS, due to their weakening and the time others

spend giving them care. According to Shah et al (2001) in his study on Production Systems, there

was evidence that out of 310 households over 70% of households affected by chronic sickness

experienced a loss of labour, 45% experienced delayed agricultural operations, 23% left the land

fallow, 26% experienced changes in crop mix and 36% experienced changes in source of

livelihood. The timing and duration of the sickness (pre and post harvest), multiple stresses and

relative economic status were found to be the most critical factors determining the intensity of

the impact. Women in patrilocal villages were reported to be more vulnerable than in matrilocal

villages.

Barnett and Blaikie (1992), published research undertaken in the Rakai and Kabale districts of

Uganda to identify the effects of HIV and AIDS on households and farming systems. The

research focused on the effect of labour losses and mapped the relative vulnerability of different

farming systems. The main conclusions were that, some farming systems would contract in areas

cultivated, productivity and range of crops because of labour shortages and that some child

headed households were emerging.

The impact of mortality on household demographics may be much more severe when the adult

death is due to HIV and AIDS than with other causes of death. Two person-years of labor may

be lost because of the weakening of the person and the amount of time spent caring for him or

her before death (FAO 2003a). Adverse dependency ratios were observed in households with the

death of an HIV-positive adult but not with the death of an HIV-negative adult, and there was a

significant association between child-headed households and adult death from AIDS (Menon et

al. 1998). Floyd et al. (2003), in a retrospective cohort study in Malawi, investigated the effect of

HIV on household structure over more than ten years. At the time of the follow-up survey, only

one in five marriages in which one partner was HIV positive at the outset was still intact.

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Children of HIV-positive parents were less likely to be alive and resident in the district than

children of HIV-negative parents.

(b) Gender implications

Gender is the differences between women and men within the same household and within and

between cultures that are socially and culturally constructed. These differences are reflected in:

roles, responsibilities, access to resources, constraints, opportunities, needs, perceptions, views,

etc. held by both women and men. (Moser, 1993)

Women play a major role in all developing countries in the different aspects of agricultural

production i.e. subsistence crops, market gardens, cash crops and animal production (Muchopa

et al 1999). Although their work is largely unacknowledged, women are the major food

producers, accounting for approximately half of the communal farmers. Although men and

women participate in most agricultural tasks, men predominate in land preparation, ploughing

and pest control; women are primarily engaged in watering, planting, fertilising, weeding,

harvesting and marketing, firewood gathering, food processing and preparation, cooking and

domestic work, activities that are typically labour intensive. Hence women in agriculture can be

considered as an untapped source of agricultural growth (Muchopa et al 1999). Various studies

that have been done so far indicate that women spend more labour in the production of food

crops especially those intended for consumption than men. Apart from food production women

are solely responsible for food processing, preservation and storage. Alvord, (1929) and

Holleman, (1952) revealed that women were the major food providers and participants in the

labour force within the communal mode of production. Boserup. E. (1970) also described

Southern Africa as a region of female farming par excellence. In rural Africa, in studies that were

done by Neema (1999) and Quisumbuig et al (1998) revealed that women account for 70% to

80% of food production.

Traditionally, rural women have always had a triple role to play in society. These roles are

differentiated as reproductive, productive and community roles (MOHCW, 2003) The study by

Laver (1995), showed that in comparison to men, most women operate small-scale farm

businesses and earn low income from agriculture; they are severely overburdened and work

longer hours in their triple roles of production, reproduction and community work. Female-

headed households are usually poorer; fewer rural female-headed households own agricultural

productive resources and their household incomes are 40% less than rural male-headed

households. HIV and AIDS therefore exacerbate existing constraints already faced by women

farmers. The advent of HIV and AIDS has further expanded the care giving role as women are

required to or expected to take care of those who are sick with HIV and AIDS related illnesses.

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The primary impact of HIV and AIDS on crop production is reduced yields, because the women

are unable to perform all the crop production activities. Labour intensive activities such as

weeding and harvesting suffer severely. The resulting decline in output may have important

implications on the food security status of the household and income from crop enterprises.

Similarly, livestock enterprises relying heavily on female labour may suffer from low production.

Affected female headed farming households may suffer severely in the short run through AIDS

related production losses in food and income. They might be forced to compromise the longer-

term survival by taking steps to offset emergent consumption needs. Some of which includes:

Sale of assets such as equipment, livestock and household items. This might have

detrimental implications on long-term agricultural production.

Borrowing to meet the short-term household consumption requirements, which again

means that the household is engaging in future debts that might deepen the crisis.

Reduced and diversified consumption when households are forced to cut back the

number of meals eaten each day. This has important implications on the health of the

family and any continued agricultural production.

A study which was done in Kagabiro village in Tanzania revealed that when a household included

someone with HIV and AIDS, 29% of the household labour was spent on AIDS related matters

and in two thirds of the cases women were devoted to nursing duties and in average the total

labour that was lost to households was 43%. This affects yields that are produced since labour

and time that would otherwise have been used productively in the fields or doing agricultural

work is transferred to caring for the sick.

The Committee on World Food Security (2001) research in Tanzania found that women spent

60% less time on agricultural activities taking care of their ill husbands. Yamano and Jayne,

(2004) in a 2-year panel of 1,422 Kenyan households surveyed in 1997 and 2000 revealed that

household size declined by 0.64 persons among households with adult death compared to the

control group indicating partial replenishment. Larger reduction in household size due to female

death than male death was observed. No change was found in total area cropped between

households incurring and not incurring an adult death. Households incurring a male adult loss

reduced land devoted to high-value-added crops. Those incurring the death of a female spouse or

head reduced the size of cultivated area devoted to cereals. The death of household heads and

spouses adversely affected the value of total crop output per acre.

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Both the quantity and quality of farm household labour are reduced through incapacitation or

death. Researchers and scholars generally agree that the infection rates are higher among women.

Since women account for 70% of the agricultural labour supply and as much as 80% of food

production, HIV and AIDS prevalence among women registers negatively on the quantity and

quality of labour and on farm output (Baier, 1997). In addition the care time devoted to the

patient ill due to AIDS by the healthy members of the household robs agriculture of labour.

While this applies to most diseases such as malaria, from which African smallholder farmers

suffer, the effects of HIV and AIDS are more telling because of the its long-term impact. Malaria

may be treated and overcome within days of effective treatment so that the patient returns to his

work, this is not the case with HIV and AIDS, which may linger for several years with or without

treatment, and during which time the infected is perennially incapacitated.

(c) Mobility and disintegration of household members

HIV and AIDS have increasingly becoming a factor influencing migration and mobility in Africa.

HIV and AIDS have become so all-encompassing for individuals, household and communities

that it seems to generate new forms and different mixes of population mobility. One clear focus

of mobility associated with the households of those who die from HIV and AIDS is the prospect

of substantial changes in composition of households: some households lose their cohesion on

the death of the household head and may dissolve, with spouse and children of the deceased

having different social obligations; others may gain labour to replace the loss of one member,

perhaps with the ‘fostering’ of the much increased number of orphans.

Some factors that induce movement include:

HIV positive people commonly returning to live with family members to obtain care and

treatment.

Others migrate in order to provide care to family members living elsewhere (Young and

Ansell, 2003).

Migration by other household members to seek income-earning opportunities especially

after the loss of a household's income though mortality and morbidity of the

breadwinner(s),

People diagnosed with HIV or displaying physical evidence of disease may migrate to

avoid stigmatization by their communities,

Children that are orphaned by AIDS may migrate to live with relatives or to seek their

own income-earning opportunities;

and widows or widowers may migrate upon the death of their partner. The tradition of

“wife inheritance” in some African societies means that a widow becomes the wife of

her late husband's brother, which may require relocation. Other women or men choose

Draft

to move after the death of a spouse, perhaps to join biological family elsewhere. The

death of a husband can lead to wife losing access to land and thus livelihood, forcing her

to move elsewhere to seek a new life.

Research by various scholars done in Southern Africa has found a similar pattern where

households experiencing adult mortality tend to become permanently smaller than other

households (Janjaroen 1998; Menon et al. 1998; Yamano and Jayne 2004) as some household

members leave following an adult death. In Uganda, for example, household size fell by 1.7

members on average in households that experienced death, compared to a decline of 0.1 persons

in other households (Menon et al. 1998). Changes in household size and composition following a

death are sensitive to the age, gender, and position of the deceased adult. In Kenya, when a

female adult died, children were frequently sent to live with relatives, whereas the death of a male

household head often led to daughters leaving the household on marriage (Yamano and Jayne

2004). Similarly, in a recent study in Mozambique, Mather et al. (2004a) found that after a female

prime-age death, it is likely that children will leave the household and a new female adult will

arrive. Some households dissolve after a prime-age adult death. The death of a male head of

household in Tanzania is more likely to cause dissolution of the household than the death of a

female head (Urassa et al. 2001). Hosegood et al. (2003) in rural KwaZulu Natal, South Africa,

found that 5 percent of 10,490 observed households experienced at least one AIDS-related death

during the one-year observation period. These households were three times more likely to

dissolve than other households.

In Uganda, Ntozi (1997), in a retrospective study of the migration of spouses and other

household members, found that 37 percent of widows and 17 percent of widowers migrated

from their original homes (spousal death from AIDS-related causes ranged from about 50 to 60

percent). Younger spouses and those in worse health were more likely to leave. Women were

more likely to leave because they were generally not entitled to inherit the land, and their kin

often lived elsewhere. Even when it does not dissolve the household, death may cause dislocation

of families: among the matrilineal people in rural Zambia, for example, women return with their

children to their own mothers’ villages (Drinkwater 1993). In studies in Kenya and Mozambique,

households were often unable or unwilling to replace their adult members after an adult death

(Yamano and Jayne 2004; Mather et al. 2004a).

In contrast, Rwandan households with an adult death were able to maintain their labour supply

through addition of new members (Donovan et al. 2003). In Mozambique, households were

more likely to hire or share labour after male deaths than after female deaths. Death of a

household head increased the likelihood of the use of child labour. One interesting finding of

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Michigan State University’s comparative study of Kenya, Malawi, Mozambique, Rwanda, and

Zambia was that, in four of the five countries, a majority of deceased prime-age adult deaths were

not household heads or spouses (Mather et al. 2004b). This observation explains the low

household dissolution rates in these countries. The authors suggest that the potential effect of

prime- age mortality on agriculture may thus be less than is predicted by other studies, given that

household heads and spouses tend to be the household members most heavily involved in

agriculture. The demographic group most affected was younger female dependents.

Urassa et al, (2001) in his study on the Impact of AIDS pandemic on mortality and household

mobility in Mwanza Region, Tanzania found out that in 44 percent of households in which the

head died, all members moved out of the household. Hosegood, Herbst and Timaeus, (2003) in

their study also found that, household instability was significantly associated with younger heads,

female heads, and death of a household member. Five per cent of the households experienced at

least one AIDS related death during the period of observation. These households were nearly

three times more likely to dissolve than other households. Child-headed families were found to

be rare. Household size decreased due to both the death of a household member and out-

migration of surviving members. Janjaroen, (1998), in a cross-sectional comparison of 324

households with AIDS related deaths, non-AIDS related deaths, and no deaths found out that

households that experienced an adult death were almost a full individual smaller than they had

been prior to the death. Deaths of adult female had a stronger negative impact on consumption

than deaths of adult male.

Overall, it is apparent that there are new mixes of forms of movement in HIV and AIDS affected

populations. The mobility generated by the excess mortality is clearly of major economic as well

as social importance. However, these outward migrations are not always negative but could be

evidence of still functional social support systems of a society in the face of the catastrophic

economic effects of increased adult mortality.

(d) Impact on agricultural extension services

Agricultural extension is the process of transferring information and technology to farmers for

use in the production process and similarly transferring information from farmers to researchers

to solve the problems of farmers (Swanson, 1984). The extension process has been clearly

expressed as a two way process where extension agents transfer knowledge and ideas to farmers

whilst on the other hand being receptive to farmers’ ideas, suggestions and problems so they can

be incorporated into the extension message (Rukuni and Eicher, 1994). HIV and AIDS takes a

heavy toll on national development staff. Agriculture extension services usually provided to the

farmers by government are disrupted as the staff responsible for these activities become ill and

Draft

die. Provision of care to sick family members, bereavement and compassionate leave and

observation of mourning times further reduce the staff's productive time.

Dry land and irrigation schemes in Zimbabwe have experienced extension staff shortage due to

HIV and AIDS. In a study on the impact of HIV and AIDS on Smallholder Agricultural

Production that was conducted in Gweru by Ncube (1998) revealed that in the whole of

Smallholder Agricultural Production Area (SHAPA), five extension workers died each season

because of the AIDS related illnesses which is about 15 percent of the total number of extension

workers in SHAPA. These deaths left some areas unattended for a long time, negatively affecting

productivity (Ncube, 1998). This led to 79.1hectares of maize crop, 7.9 hectares of sunflowers

and 2.3 hectares of groundnuts remaining uncultivated. In Uganda, disruption in services due to

illness and death has led to an informal reduction of the length of the staff working week

(Topouzis, 1998).

By one estimate, approximately two person-years of labour are lost by the time one person dies

of AIDS. According to FAO, AIDS has killed about 7 million agricultural workers since 1985 in

the 25 hardest-hit countries in Africa, and it could kill 16 million more before 2020. The loss in

the agricultural labour force through AIDS in the nine hardest-hit African countries, for the

period 1985-2020, was projected as follows: Namibia 26 percent; Botswana 23 percent;

Zimbabwe 23 percent; Mozambique 20 percent; South Africa 20 percent; Kenya 17 percent;

Malawi 14 percent; Uganda 14 percent; United Republic of Tanzania 13 percent (FAO, 2001).

A study in Zambia and Uganda (IFAD 2001), discovered that:

a) Increased funerals in the communities were leading to cancellation or postponement of

expensive planned activities and make impossible timely attainment of programme

targets.

b) Families directly affected by AIDS related sickness or death were prevented from

participating in group to organise extension activities through lack of adult

representation or the shift in family priorities towards caring for the sick or searching for

food rather than attend extension meetings.

c) Illness and death of staff and extension contact farmers/ community organisers lead to

loss of expensively attained knowledge and experience and low adoption of technologies

and agricultural innovations. In one district office of Zambia, four of the 22 extension

staff members had died in the one year prior to the mission and three of these, according

to the officer who reported this incident, were AIDS cases and similar high staff

mortality was reported in Uganda.

d) Increasing staff workload through the need to train community workers, group leaders,

Draft

and farmers to replace those trained but ill or dying off or need to attend to AIDS

related eviction of orphans and widows from land and property.

e) Increased domestic pressure, low incomes of staff, trauma and burn out on account of

having to look after sick relatives or attend funerals.

Although systematic surveys are not available, it is probable that agricultural extension workers

have higher levels of HIV than the general population. They are mobile and relatively affluent in

poor communities, which are known risk factors to HIV. It is probable that they are dying more

quickly than they can be trained. In a number of countries, agricultural extension services are on

the verge of collapsing entirely because of the HIV and AIDS pandemic. The pre-existing

weakness of the services predisposed them to this structural crisis. (DFID, 2003)

The high HIV and AIDS related deaths among Ministry of Agriculture (MoA) staff in Eastern

and Southern Africa (ESA) is likely to have negative impacts in the fight against the pandemic. In

Kenya’s MoA, 58 percent of all deaths in the late 1990s were thought to have been AIDS-related

(GTZ: 1999). In Malawi in 1998, at least 16 percent of the staff of the Ministry of Agriculture

and Irrigation (MoAI) were reported to be living with HIV and AIDS, 76 percent had lost at least

one colleague, and 60 percent had lost at least one close relative to AIDS (Bota et al. 1998, cited

in Topouzis 2003). In Zambia, 67 percent (of 155) agricultural extension workers interviewed had

lost at least one co-worker to HIV and AIDS in the three years preceding one study (Alleyne et

al. 2001). Studies have also reported reductions in agricultural extension service time due to HIV

and AIDS. Haslwimmer (1994) in Uganda reported 25 to 50 percent reductions in agriculture

extension time. In the mid-1990s, Haslwimmer (1994) found that up to half of agricultural

extension staff time in one district in Uganda had been lost to HIV and AIDS. Staff members

were frequently absent from work because they had to care for sick relatives or attend funerals,

or were sick themselves. Organizations in areas with a high HIV and AIDS prevalence are

characterized by high absenteeism, high turnover, a loss of institutional memory, and reduced

innovation. As individuals in government and NGOs continue to die, the capacity gap between

what is needed and what can be delivered is becoming an abyss.

2.3.2 Financial Capital

(a) Changes in household financial capital assets

Financial capital refers to the financial resources that people use to achieve their livelihood

objectives, including stocks (savings, convertible assets, including livestock) and flows of income.

The loss of human capital would lead directly to a loss of financial capital. Household incomes

Draft

declines especially if, as stated by Stokes, HIV infections and AIDS related deaths are

disproportionately concentrated in the most productive age groups (15-49 years). This income

decline from farm and off-farm sources further renders rural households vulnerable to food

insecurity. As productive assets are sold off, the household's future livelihood is jeopardized.

Among the financial capital effects thought to be influenced by the pandemic are reductions in

income from farm and off-farm sources, liquidation of savings accounts, seeking of remittances

from family, changes in degree of reliance on off-farm income among male, orphan and female-

headed households, changes in wage earnings among female-headed households, changes in

income-generating activities among female-headed households (Topouzis 2000), sale of stores of

value (jewellery, household goods), borrowing from informal sector (Mutangadura et al. 1999),

borrowing from rural traders or money lenders (often at exorbitant interest rates), exhaustion of

credit resources, sale of livestock, increased expenditure on health care, transport and funerals

and reduced expenditure on agricultural inputs.

It should be noted that the sale of livestock appears under several asset rubrics and illustrates the

difficulty in classifying some effects under only one category. While livestock are generally

thought of as part of natural capital, they also operate as a store of wealth in many societies in

which financial markets are underdeveloped. Moreover, by providing animal traction power, they

also operate much like physical capital assets. Disposal of draught livestock directly affects the

household's productive activities and increases the risk of food insecurity.

(b) Changes in household income, expenditure and consumption patterns

In a cross-sectional comparison of households with and without an HIV-positive individual in

Free State, South Africa, per caput income in AIDS-affected households was 50% to 60% that of

unaffected households (Booysen and Bachmann 2002). In another cross-sectional survey of 680

households in Limpopo province, Oni et al. (2002) made similar observations. In a five-year

retrospective study of 232 urban and 101 rural AIDS-affected families, Nampanya-Serpell (2000)

reported a decline in monthly disposable income of more than 80 percent in more than two

thirds of the AIDS-affected families, with higher losses following a paternal death. But Urassa et

al. (1997) found that in Tanzania, households with orphans did not have a lower economic status

than those without orphans (though this may be a positive selection bias, as households with

greater resources are more likely to foster orphans).

Reducing food consumption quantity or quality may be a highly erosive “coping” strategy, as

nutrient requirements rise following HIV infection. In a panel study in Indonesia, Gertler et al.

(2003) showed a prime-age male death to be associated with a 27% reduction in mean per capita

household consumption, whereas the death of a female had no significant impact. In Mexico,

Draft

they found the death of a prime-age adult household member to reduce per capita consumption

by nearly 8 percent, with no significant gender differences. In Côte d’Ivoire, Bechu (1998)

surveyed 107 households with at least one adult ill with AIDS related illnesses and with one or

more children and interviewed them six times at two-month intervals. The data was compared

with the results of a study conducted in Yopougon in May 1992 and based on a sample of 2,064

households. The study found per capita consumption of AIDS-affeccted households to be half

that of other households. In a cross-sectional survey of 119 households in the Rungwe district of

Tanzania, Mwakalobo (2003) found that households that experienced an AIDS related death

spent substantially less on food than other households. HIV and AIDS related death significantly

increased the probability of a household falling below the poverty datum line. In South Africa,

average monthly per capita food expenditure of affected households was 70 percent to 80

percent less than that of other households (Booysen and Bachmann 2002), but no significant

difference was found in total monthly expenditures, most likely because of rises in health-related

expenditures. Many studies show that households experiencing adult death tend not to recover to

pre-shock levels of consumption (e.g., Yamano and Jayne 2004; Gertler et al. 2003; Bechu 1998).

Such a lack of resilience is likely to increase vulnerability to other shocks to food and nutrition

security.

AIDS-affected households do tend to incur high health-care expenditures (Tibaijuka 1997 in

Tanzania; Booysen and Bachmann 2002 in South Africa). Bechu (1998) in Côte d’Ivoire found

that health-care costs specific to the person with AIDS accounted for almost 80 percent of the

household health-care budget. In the Rungwe district of Tanzania, rising medical expenses or an

HIV and AIDS-related death significantly increased the probability of a household’s falling below

the poverty datum line (Mwakalobo 2003).

A study by Menon et al (1998) revealed that a decline in household durable goods was only in

households with HIV-related deaths. This effect was more pronounced in agricultural than in

trading villages. Bechu, (1998), in his study on the Changes in household expenditures and

consumption due to illness and death of a household member from HIV and AIDS in Cote

d’Ivoire found out that, consumption among the AIDS affected households was only half that of

the comparison group representative of the general population. The portion of the budget spent

on health care in AIDS related households was almost double that of the households in

Yopougon. Although a slight increase in consumption was observed after the initial shock of

death, the households did not return to earlier levels of consumption. Health costs for the sick in

the AIDS affected households accounted for almost 80 percent of the health budget. But once

the illness was identified and there was access to health care, most of the sick seemed to distance

themselves gradually from the structures of modern care – and to a lesser extent from traditional

Draft

medicine – by cutting back on hospitalisation, medical consultations and medicine. Oni et al,

(2002) revealed that HIV and AIDS affected households had lower annual income, were smaller

in size, had lower savings and spent more on transportation, funerals and health care but less on

housing, remittances and education than unaffected households. The coping strategies adopted

by affected households included sale of household assets, withdrawal of children from schools

and joining community support groups. Nampanya-Serpell, (2000) found out that a decline in

monthly disposable income of more than 80 percent was observed in more than two thirds of the

AIDS affected families, especially following paternal death. According to Booysen and

Bachmann, (2002) household members, mainly those who were unemployed, spent an average of

7.5 hours per day providing care during the fatal illness of the deceased. Per capita adult

equivalent income in affected households was only between 50-60 percent of the levels of

income in non-affected households. The average monthly food expenditure of affected

households was 70-80 percent less than of that of the unaffected households, although no

significant difference was found in total monthly expenditures.

Therefore, from the empirical evidence presented it can be seen that taking care of a person sick

from AIDS related illnesses is not only an emotional strain for household members, but also a

major strain on household resources. Loss of income, additional care-related expenses, the

reduced ability of caregivers to work, and mounting medical fees push affected households

deeper into poverty. It is estimated that, on average, HIV-related care can absorb one-third of a

household’s monthly income (Steinberg M. et al. October 2002).

(c) Changes in household investment choices

Loss of income and unplanned additional care-related expenses adversely affects household

investment decisions such as investments into human capital e.g. education, agriculture, financial

assets e.g. savings, physical assets, etc.

Many studies have reported the negative effect of HIV and AIDS on children’s schooling (Urassa

et al. 1997; Gilborn et al. 2001; Deininger et al. 2003; Gertler et al. 2003). Deininger et al. (2003),

in an analysis of a panel data set of 1,300 households included in surveys conducted in 1992 and

2000, showed that foster children were at a distinct disadvantage in both primary and secondary-

school attendance before the introduction of universal primary education. In Uganda, in a

descriptive analysis of a baseline survey of 353 HIV-positive parents, 495 children of People

Living With HIV and AIDS(PLWHAs) 233 orphans, and 326 guardians, Gilborn et al. (2001)

found declining school attendance among 28 percent of the older children of PLWHAs, whereas

it was improving for 21 percent of older foster children. In a recent study, Case et al. (2004) using

19 Demographic and Health Surveys (DHS) conducted between 1992 and 2000 in 10 sub-

Saharan African countries, showed that although poorer children were less likely to attend

Draft

school, poverty alone did not account for the lower enrollment of orphans. Orphans were less

likely to be enrolled than are non-orphans with whom they live. The lower enrollment of orphans

was largely explained by the greater tendency of orphans to live with distant relatives or unrelated

care-givers.Yamano and Jayne (forthcoming) found the negative impact of adult mortality on

school attendance in Kenya to be more severe in poor households, as did Nampanya-Serpell

(2000) in urban but not in rural areas of Zambia. Yamano and Jayne (forthcoming) also found

out that adult mortality was negatively affecting schooling even in the period directly before the

death, most likely because children were sharing the burden of care giving. Again, the type of

orphan hood seems to matter. In Indonesia only maternal death resulted in delayed school entry,

whereas paternal death increased the dropout rate.Exactly the reverse occurred in both cases in

Mexico (Gertler et al. 2003).

(d) Sustainability of household food and nutrition security (food accessibility and utilization)

Food security is the availability of food, access to food and the absence of risk related to either

availability or access. Most people in the SADC region derive their household food security from

crop and livestock agriculture. About 70 percent of the SADC population is engaged in crop and

livestock production. As a result, increases in farm output and productivity enhance food and

income security. But the adverse effects of HIV and AIDS have resulted in labour deficits and

the sale of agricultural output to meet household medical costs, leaving the household food

insecure. According to Barnett and Rugamela (2001), households are said to be food secure if

four factors are in balance. These are food availability, equal access to food, stability of food

supplies and quality of food. HIV and AIDS affect all these factors thus reducing food security.

IFAD (1996) describes household food security as ‘the capacity of households to procure a

sustainable and stable basket of adequate food’.

Food storage and processing activities are impaired when a household is affected by HIV and

AIDS. This also impacts on the availability of seed for subsequent cropping. Households

normally spend some time engaging in off-farm activities that enable them to earn some income.

In the case of urban areas most households meet their food needs through purchase of food

using income earned from formal employment. HIV and AIDS reduce this income given that the

infected become less productive and the affected are forced to tend to the sick. In essence this

reduces household’s purchasing power leading to a vicious cycle of food insecurity and poverty.

At the micro level HIV and AIDS reduces the ability of the household to produce and buy food,

depletes assets and reduces the household income and purchasing power thus reducing labour,

management of farm resources and skills and reducing the productivity of current workers thus

affecting food security.

Draft

Barnett and Rugalema (2001), Mutangadura et al (1999; 2000) cites the serious depletion of

human resources as one of the major impacts of the disease on agriculture. HIV and AIDS

results in the loss of experienced agricultural workers, which affect both individual households

and communities, resulting in labour shortages and declines in productivity both on and off the

farm. A decline in productivity leads to declines in household income through both decreases in

the household's own production and through declines in off-farm income and remittances. As is

clear from the preceding points, a decline in the quality and quantity of food can often be

expected. The incidence of increases of orphans and the food consumption of all surviving

household members often declines when an adult dies. In addition to these effects, which are

owing to the loss of labour, household food security can also be reduced through an increase in

the number of mouths to feed arising from the fostering of children or the hosting and caring of

sick relatives. Mwakalobo (2003) discovered that households experiencing AIDS death spent

substantially less on food than those not experiencing death. Logistics regression results revealed

that HIV and AIDS related death significantly increases the probability of a households falling

below the poverty datum line.

In households coping with HIV and AIDS, food consumption generally decreases. The family

may lack food and the time and the means to prepare some meals, especially when the mother

dies. Research in Tanzania showed that per capita food consumption decreased 15 percent in the

poorest households when an adult died. A study carried out in Uganda showed that food

insecurity and malnutrition were foremost among the immediate problems faced by female-

headed AIDS-affected households. For the patient, malnutrition and HIV and AIDS can form a

vicious cycle whereby under-nutrition increases the susceptibility to infections and consequently

worsens the severity of the HIV and AIDS condition which in turn results in a further

deterioration of nutritional status. Even when a person does not yet show symptoms, infection

with HIV may impair nutritional status. The person may lose their appetite, be unable to absorb

nutrients and become wasted. According to Mason et al (2003) the 2002 drought in Southern

Africa interacted with HIV and AIDS in high prevalence areas to bring about rapid deterioration

in child nutrition. However, because these effects were seen mainly in areas that previously had

better child nutrition, the effect is not obvious from averages. Underweight children increased

very substantially, for example, from 5 to 20 percent in Maputo between 1997 and 2002; from 17

to 32 percent in Copperbelt, Zambia from 1999 to 2001-2; and from 11 to 26 percent in

Midlands province, Zimbabwe from 1999 to 2002. Changes were much smaller during non-

drought periods and in areas of low HIV prevalence. These trends may be explained by direct

effects of pediatric AIDS (growth failure is occurring at younger ages) but the larger effect is

probably indirect, as drought and HIV hasten destitution in affected families. Traditionally worse

Draft

off areas appeared protected perhaps because of food assistance. Though this impact remains to

be determined.

(e) Household Market Access

Rural households have diverse livelihood strategies and one of them is engaging in non-

agricultural activities, including micro enterprises (agro-processing, trading and other off-farm

occupations). Through these various activities, households seek both to ensure their food

requirements and to generate the income they require to satisfy their immediate consumption

needs, social purposes and investments (IFAD, 2003). Interacting with agricultural markets is

thus an important aspect of the livelihood strategies of many rural households, rich and poor

alike. Markets are where, as producers, they buy their agricultural inputs and sell their products;

and where, as consumers, they use their income from the sale of crops, or from their non-

agricultural activities, to buy their food requirements and consumption goods. Virtually all

households in rural areas are, by preference, both producers and consumers, buyers and sellers;

and many sell agricultural produce and buy their food at different times of the year. However,

rural households that, for one reason or another, are unable to interact with these markets are

prevented from adopting these diverse livelihood strategies; and indeed, in many parts of the

world, rural poor people often say that one reason they cannot improve their living standards is

that they face difficulties in accessing markets.

The issue of market access may usefully be considered according to three dimensions:

Physical access to markets: Distance to markets and lack of roads to get to them or roads that are

impassable at certain times of the year is a central concern for rural communities throughout the

developing world. It undermines the ability of producers to buy their inputs and sell their crops;

it results in high transportation costs and high transaction costs, both to buyers and sellers; and it

leads to uncompetitive, monopolistic markets. Difficult market access restricts opportunities for

income-generation whilst remoteness increases uncertainty and reduces choice resulting in more-

limited marketing opportunities, reduced farm-gate prices and increased input costs. It also

exacerbates the problem of post-harvest losses, which can reach as high as 50 percent in some

areas. In doing so, it weakens incentives to participate in the monetized economy, and results in

subsistence rather than market oriented production systems (IFAD, 2003).

Market structure: Rural markets are characterized by extreme asymmetry of relations between, on

the one hand, large numbers of small producers/consumers, and on the other, a few market

intermediaries. Such market relations are characteristically uncompetitive, unpredictable and

highly inequitable. Rural producers who face difficulties in reaching markets often become

dependent on traders coming to the village to buy their agricultural produce and to sell those

Draft

inputs and consumer goods. However, especially in remote areas, a trader may not arrive reliably

or at all, and producers are often faced with little choice but to accept the first offer of the first

trader who shows up, however unfavorable it might be. Such a situation is exacerbated when the

trader is also the only source of information on prices and other relevant markets (IFAD, 2003).

Lack of skills, organization and information: In their participation in agricultural markets, poor

producers find themselves at a major disadvantage. Many have a poor understanding of the

market, how it works and why prices fluctuate; they have little or no information on market

conditions, prices and the quality of goods; they lack the collective organization that can give

them the power they require to interact on equal terms with other, generally larger and stronger,

market intermediaries; and they have no experience of negotiation and little appreciation of their

own capacity to influence the terms and conditions upon which they trade. With little experience,

no information and no organization, they have no basis upon which either to plan a market-

oriented production system or to negotiate market prices and conditions. Ultimately, their lack of

knowledge means that they are passive, rather than active, players in the market; that they can be

exploited by those with whom they have market relations; and that they fail to realize the full

value of their production (IFAD, 2003).

For these reasons, improved market access is not an issue of consequence only to better-off

producers, and it is not relevant only to cash crop, rather than food crop, production. It is of

importance to all rural households including HIV and AIDS affected households, and assisting

such households in improving their access to markets must be a critical element of any strategy to

enable them to enhance their food security and increase their incomes (IFAD, 2003).

2.3.3 Physical Capital

(a) Changes in household productive physical capital assets

Physical capital comprises the basic infrastructure and producer goods needed to support

livelihoods e.g. buildings, roads/ transport, water supply, and other communications. The

productive equipment that the households use in pursuit of their livelihoods also comes under

threat with HIV and AIDS (Gillespie and Haddad, 2001). Households' physical capital refers to

those tangible assets and producer goods other than their natural capital, i.e., housing, household

goods, furniture, tools and equipment, as well as livestock. Once savings and credit resources

have been exhausted and liquid assets have been disposed of, households resort to selling of

other assets (Stokes, 2003). The disposal of physical assets and equipment needed for agricultural

production means that rural households' ability to generate income and sustain their families in

the short term is reduced.

Draft

Donovan et al, (2003) observed that attempts by households to make up for lost income included

distress sales of household assets and livestock, increased dependency on natural resources for

food and income, and the establishment of clubs for group income generation. Rugalema (1999)

also noted that AIDS-induced illness consumes cash, productive assets, and social claims,

particularly the use of external labour. Funerals deplete resources of afflicted and affected

households.

Livestock activities might be jeopardized by loss of time to take care of the livestock, resulting in

death of livestock due to poor management. Frequent slaughters and sale of livestock to finance

medical care for AIDS related illnesses also lowers livestock productivity and has detrimental

effects on crop production (Engh et al. 2000; Haslwimmer 1994). For example in Rakai, Uganda

65 percent of 752 households with AIDS related deaths reported selling property to cover

medical treatment and burial costs (Konde-Lule et al., 1996). In another research in Zimbabwe,

Kwaramba (1999) indicated that AIDS affected households experienced a decrease in cattle and

goat numbers of 26 percent and 3 percent respectively due to livestock sales to meet treatment

costs. Given the importance of draft cattle to agricultural production, this severely compromises

the smallholder farmer’s ability to sustain agricultural production. The effect in agricultural

production could be further exercebated by the fact that after a male death, widows and children

are left to take care of the livestock and they often lack the management skills to do so

effectively, further eroding this asset (Engh et al, 2000 and Haslwimmer, 1994).

(b) Changes in optimal farm-household production decisions

Many studies in sub-Saharan Africa, particularly over the last three to four years, showed the

vulnerability of subsistence agriculture to the impacts of AIDS. These include reductions in the

area of land under cultivation and crop diversity, abandonment of specific activities and crops,

shifts to less labor intensive mono-cultivation, use of minimum-tillage techniques, and reduced

livestock use (e.g., FASAZ/FAO 2003; NAADS 2003; Drimie 2003). Below is a summary of the

main findings from different studies:

In a retrospective study from Kenya, Yamano and Jayne (2004), using a panel of 1,422 Kenyan

households surveyed in 1997 and 2000, found the death of a prime-age male household head to

be associated with a 68 percent reduction in per capita household crop production value. Adult

female mortality caused a greater decline in cereal area cultivated, whereas prime-age male adult

death resulted in a greater decline in cash crops such as coffee, tea, and sugar and nonfarm

income. Shah et al. (2001) made similar observations in Malawi.

Draft

In her study Black-Michaud, (1997), compared Burkina Faso and Cote d’Ivoire examining the

links between savannah and forest zone systems and migration. In Burkina Faso she found a

reduction in cultivated area and changes to the agricultural calendar apparently because of

reduced remittances due to the illness or death of a migrant worker, rather than due to local

illness and death among smallholder farmers themselves. In Cote d’Ivoire, however, illness and

death in village farm households were having a serious impact. Common to both countries were

the findings that cash crops were reduced before food crops and that the total area under

cultivation declined. In Rwanda, Donovan et al. (2003) in their descriptive analysis of a cross-

sectional study with a four-year recall of household mortality information also found that 60

percent to 80 percent of rural-study households suffering illness or death reported reduced farm

labor and land cultivation following death of a male head.

In Swaziland, Muwanga (2002) found a reduction of 54 percent in maize production following

the death of the household head. In Malawi, Shah et al. (2001) found 70 percent of the

households affected by chronic sickness to be suffering from labor shortages, with 45 percent

delaying agricultural operations and 25 percent leaving land fallow or changing the crop mix.

Empirical research in Zimbabwe indicate higher decreases in cash crop production such as

cotton compared to traditional crops such as maize and groundnuts for households which

experienced a death of a bread winner due to AIDS (Kwaramba, 1997).

In a reconnaissance survey of 220 households, followed by an in-depth study of ten households

affected by AIDS, Tibaijuka (1997) reported significant losses in agricultural production due to

labor loss, and reallocation of labor to nurse the ill. In Uganda, in an in-depth qualitative survey

in three communities at different stages of HIV and AIDS impact and different farming systems,

Barnett et al. (1995) found a progressive decline in production and socioeconomic status among

affected communities. In Mozambique, a nationally representative survey with recall data on the

deaths, departures, and arrivals of household members between 1999 and 2002 found that

affected households had smaller total and cultivated land areas, particularly following the death of

a male household head. But cultivated area per adult equivalent of the households experiencing

death was similar to that of unaffected households because of net out migration (Mather et al.

2004a)

Thus the overall observation from the literature is that HIV and AIDS related losses in labour

may have an overall negative impact on crop production in terms of area cultivated, yield levels

achieved and working capital devoted to agriculture leading to major changes in the cropping

patterns of the affected households.

Draft

2.3.4 Natural Capital

(a) Environmental Degradation and Changes in Household productive natural capital asset base

Natural capital encompass the natural resource stocks from which resource flows and services

useful for livelihoods are derived e.g. lands, trees, water sources. The loss of human and financial

capital can have important effects on a household's use and preservation of its natural capital.

HIV and AIDS can result in serious deterioration in the natural capital of households as the

declines in their human and financial capital could limit their ability to invest in maintaining and

improving their land base. Despite the fact that land is the most important primary natural asset

that rural households possess, adversely affected families end up selling or disposing off their

land. Stokes (2003), identified the following natural capital assets that can decline in the presence

of HIV and AIDS:

Reductions in soil fertility,

Declines in on-farm conservation and/or irrigation practices,

Decreased biodiversity due to asset stripping, selling of firewood, increased harvesting of

wild food, game, etc,

Renting or leasing out portions of the household's landholdings,

Appropriation of land by relatives (taken from widows, orphans) and

Sale of land

Each of the declines in natural capital reduces the household's ability to cope with the effects of

HIV and AIDS.

According to Odenya (2003), weeding and other inter-cultivation measures may be neglected as a

result of labour and input shortages. Some families may abandon traditional practices such as

mulching which replenish the soil, or may sell livestock which would otherwise provide manure,

thus reducing soil fertility. About 60 percent of respondents indicated that soil fertility had

declined, and greater exploitation of fuel wood for sale and wild foods for home consumption

were resulting in increased deforestation and the increased scarcity of wild foods.

In a study by Zakhe Hlanze et al (2005) titled: Impact of HIV and AIDS and Drought on Local

Knowledge Systems for Agro Biodiversity and Food Security, the results showed that in Swaziland

increase in morbidity results in indiscriminate exploitation of natural medicinal plants to cure

diseases and HIV and AIDS. Women and children are sometimes deprived of access to natural

resources upon the death of the man e.g. when a man dies land is reallocated by the chief.

Draft

2.3.5 Social Capital

(a) Social Support networks

Social capital refers to the social resources upon which people draw in pursuit of their livelihood

objectives, including networks, membership of formal and informal groups, and relationships of

trust and reciprocity.

The illness and death of household members can disrupt a household's links to their extended

family and the larger community (Stokes, 2003). On the communities the death of a male of a

household could seriously impair a household's ability to access community resources or even

receive family support. Some of the most common social impacts of the pandemic include:

Increased reliance on extended family and formal and informal community

organizations for agricultural production, housework, child care, and fostering

Increased reliance on community willingness to support educational and nutritional

needs of orphaned children (e.g. school fees, uniforms, and supplemental feeding)

Less time to participate in social and cultural activities

Possible disintegration of household (Gillespie et al. 2001; Stokes 2002; Harvey 2004).

At a household level, morbidity and mortality due to HIV and AIDS affect household livelihood

resources and assets, resulting in a reduction of the ability of the household to generate livelihood

and adjust to future shocks. Loss of human resource (labour), other resources and assets hinders

household participation in various social networks and groups. In areas where cultural practices

limit women's participation in formal organizations outside the home, the death of a male

breadwinner can seriously impair a household's ability to access community resources or even

receive family support. Nonetheless, studies indicate that households affected by HIV and AIDS

draw their support primarily from family, neighbors, community institutions and informal

organizations (Mutangadura et al. 1999). Thus, the social capital of households operating through

their relationships with extended kin and the community is critical to their ability to recover from

the illness and/or death of a household member due to HIV and AIDS.

At a community level social capital can have major impacts on mitigating the effects of HIV and

AIDS. Communities with high levels of social capital can provide affected households with a

variety of social support activities that permits families to adjust to the illness or loss of members.

Conversely, communities with low levels of social trust and solidarity can leave households and

families to fend for themselves or even to isolate and ostracize those households afflicted with

HIV and AIDS. According to Bernett and Whiteside, (2000), susceptibility and vulnerability are

Draft

determined by two variables, that is., the degree of social cohesion and the overall level of wealth

of the society. Four broad types of society were distinguished, each with a distinctive pattern of

HIV prevalence. Social cohesion can be strengthened in four areas, that is, altering social norms

and standards, improving the status of women, improving the performance of social institutions

and improving the quality of controlled social environments (e.g. improving housing and social

support for migrant-labor camps.

(b) Access to behavioral change information on HIV and AIDS and Agriculture

Access to information by household members as far as HIV and AIDS and agriculture affects the

vulnerability of a household to the impacts of HIV and AIDS.

Behavior change information on HIV and AIDS promotes and sustains risk-reducing behavior in

individuals and communities by distributing tailored health messages in a variety of

communication channels. Households that have access to HIV and AIDS related information are

better informed on how to deal with the condition. Understanding the pandemic influences the

kind of coping strategies that are adopted by a household in the fight against HIV and AIDS.

Access to HIV and AIDS information allows households that have sick members to adopt

recommended eating practices and sexual behaviour. This reduces frequency of illness and

subsequently medical cost incurred by the household.

Another important aspect is household’s access to agricultural information. Agricultural

information affects management practices employed by the rural households. Households that

are not well informed usually adopt farm management practices that are unsustainable and make

the households more vulnerable. Information that relates to crop mixes, input usage, market

information, etc, affects agricultural activities and the productivity and efficiency of agricultural

activities. This has a bearing on how the households deal with the impacts of HIV and AIDS.

Chapter 3: Theoretical Framework to HVI Development

Draft

3.1 Approaches to HVI Index Development

Two major types of approaches were used in the development of the HVI, i.e., principal

component analysis and the Costa’s fussy set approach to multidimensional analysis of poverty

given composite indicators. These approaches though different, they compliment each other as

far as model development is concerned. Whilst the principal component analysis served as a

dimension reduction tool that was used to reduce a large set of variables to a smaller set that still

contained most of the information in the large set to facilitate HVI computation, the fussy set

approach attached a score on these indicators given the extent, nature and severity of HIV and

AIDS impact and calculated a compounded index to describe the level of vulnerability of each

household.

3.1.1 Principal Component Analysis

This analysis was used solely for refining indicators or variables, i.e., sieving out important

variables to be included in the HVI model. In this way Principal Component Analysis (PCA) was

applied more as a data reduction method to reduce the number of variables used to measure each

impact area, than as a structure (relationship) detection method.

Data from the 2004 study was stored and analyzed using a statistical package known as Statistical

Package for the Social Sciences (SPSS). PCA was done using the same statistical package. After

going through PCA of all identified variables to measure each impact area an output table known

as the Total Variance Explained appeared in the SPSS output file. This table gave the initial

eigenvalues for each component or variable. The table always appears as shown in the example

below.

Component Initial Eigenvalues Extraction Sums of Squared Loadings

Total % of

Variance Cumulative % Total

% of variance

Cumulative

1 1.3 65 65 1.3 65 65

2 0.7 35 100 0.7 35 100

Extraction Method: Principal Component Analysis

The eigenvalues indicated the amount of variance accounted for by each of the

components/variables. For example in the table above the first principal component explains the

maximum variance in all the variables -- a variance of 1.30. The second principal component

explains the maximum amount of the remaining variance -- a variance of 0.70. The two

components explain all the variance in the original variables (1.30 + 0.70 = 2). The proportion of

variance accounted for by the first principal component equals 0.65. The proportion of variance

accounted for by the second principal component equals 0.35.

Draft

A method suggested by Kaiser (1960) was used to reduce the number of variables in the data set

by finding the smallest possible set of principal components which explain most of the variance

in the data set. Kaiser suggests that only those factors whose eigenvalues are greater than 1 are

retained. Hence for the HVI model, components with the highest eigenvalues among the

components or variables suggested in each impact area were used in the computations.

3.1.2 Fussy Set Approach to Household Vulnerability Index Analysis

a) Theoretical framework

The theory proposed for the construction of the HVI largely took on from the work originally

proposed by Costa1. The quest for the exercise, as was the case in the work by Costa, was to

quantify the multi-dimension aspects of the impacts of a health problem on a household. Our

specific quest was to assess at the household level, the impact of HIV and AIDS on agriculture.

The Fussy Set approach was used to analyse the data. The following definitions help clarify how

the approach was used:

One can state that for the population N made up of n households i.e. (N={hh1, hh2, hh3

…hhn}, V is a subset of v households that have some degree of vulnerability to HIV and

AIDS- hence impacted by the epidemic. Thus v≤n and v=0 implies that there are no

vulnerable households, and v=n implies that all households are vulnerable.

One can also break down the vulnerability X into m specific dimensions of impact, and

give a corresponding weight (wi , i=1,…,m)to each dimension. The weights can be

predetermined, or developed using an appropriate function.

The vulnerability of any given household hhi i=1…n to the jth j=1,…m dimension of

impact can be expressed as Xij, and set to take values between 0 and 1 such that 0=no

impact and 1 full impact. A specific formula for calculating Xij is discussed later. Thus

each Xij denotes the degree of vulnerability of household i to the jth dimension of

impact, and Xijwi will be the corresponding weighted vulnerability.

The sum of the weighted vulnerabilities across all dimensions will give the particular

household’s total vulnerability Vhhi to HIV and AIDS, that is:

1 Costa, M. (2002). A Multidimensional Approach to the Measurement of Poverty: An Integrated Research

Infrastructure in the Socio-Economic Sciences IRISS Working Paper Series No. 2002-05; and Costa, M. (2003). A Comparison Between One-dimensional and Multidimensional Approaches to the Measurement of Poverty An Integrated Research Infrastructure in the Socio-Economic Sciences IRISS Working Paper Series No. 2003-02.

Draft

ij VhhwXm

j

wj

m

j

11

/

It is also possible to sum down the dimensions and calculate the particular dimension’s

contribution to vulnerability to HIV and AIDS.

For the HVI, the sum of the weights were conveniently set to 1001

m

j

jw . The

weights were preset as discussed below.

The Household vulnerability index was calculated by applying the theory discussed above to data

collected by household questionnaires, observing a number of steps as shown in section 3.2.

b) Setting the HVI Dimension Weights

Weights or scores for each of the five HVI dimensions are not necessarily the same across every

community, district, province or country but depend on the livelihood strategies of the

community being investigated. The weights are preset after taking into consideration the

importance of each livelihood asset in the lives of the target community. For example a

community that is well networked to a number of markets and that is actively participating in

those markets would put more weight on their financial capital compared to natural capital. On

the other hand a community that is near a rich forest and survives mainly from harvesting that

forest would also put more weight on the natural capital asset. So the contribution of the

particular livelihood asset to the community’s way of life is of importance in presetting the

weights.

3.2 Step taken in designing HVI Computations

Step 1: Developed overall framework for HVI – This involved critical reviewing of different theories

supporting vulnerability analysis and methods that have been used in the past. This formed the

foundation of the HVI conceptual thinking and proposed methodology for quantifying

household vulnerability due to an external shock.

Step 2: Linked theory to practice – Involved identification of data sources and variables that can be

used in HVI analysis. This was done by conducting a detailed literature review on the impact of

HIV and AIDS on the 15 selected impact areas. The review mainly focused on empirical

evidence that was observed through different studies in the Sub Saharan Africa. Through the

Draft

literature review several variables were identified as indicators that would be used to test each

impact area.

Step 3: Defined dimensions and identified impact areas (hypotheses) that could be used to test vulnerability - Five

dimensions of impact that is, the five livelihood assets that are affected by HIV and AIDS were

identified using results from the 2004 FANRPAN impact study. The study was able to reveal that

HIV and AIDS affect the entire livelihood of rural households such that any effort to address the

pandemic should consider all the five livelihoods assets, i.e., human, financial, physical, natural

and social capitals. These were taken as dimensions of impact. These dimensions are defined by

different impact areas that were also identified during that study and are outlined in Chapter 4.

The impacts areas help explain how vulnerable households are to each of the dimensions.

Step 4: Assigned weights and transformations to impact areas using evidence from other statistical models and

previous studies - The weights given to each impact area were determined as mentioned in section

3.1.2 (b). According to the HVI model , the sum of the weights are set at 100 so that the

individual HVIs take values between 0 and 100, with 100 being full impact on the basis of

selected dimensions. The higher the value the more vulnerable is the dimension and hence

defining impact areas within the dimension.

Transformation of selected variables was done by setting an appropriate scale so that each

variable falls between 0 and 1. This process allowed for use of a similar scale which made

comparisons of results possible. The transformation approach used depended on the variable of

interest and how information on that variable is collected. A very simple approach has been used:

an attribute of 1 is set whenever impact is felt 100%, and 0 if not. For dummy variables, that is,

simple yes or no answers this can be achieved by setting 0 and 1 according to the direction of

impact of that variable. Other values between 0 and 1 are set according to relative severity of

impact. Other more robust techniques were also used. For instance for dependency ratio, a value

Y for a "standard normal dependency ratio for the particular community say, from an unaffected

household can be used in the formula X-Y/(Max X -Y). Another approach that was used to

transform the data to 0, 1 without losing its general distribution, was by dividing by the range.

Table 3.3 shows all the transformations that were used for each variable in the HVI computation.

See Annex 1.

Step 5: Determined the contribution of each dimension/impact area to the HVI - This was computed using a

simple formula. This is given as:

Draft

Weight of an impact area to a given dimension = Extent to which a given impact area

determines a given dimension (impact coefficient) x normalized value of the variable selected to test the

impact area x the total impact score or weight for that dimension

The impact score or weight and the impact coefficients were derived through a process described

in Step 4 (b).

Step 6: Calculated, the weighted vulnerability to a given impact area (per household), and the total vulnerability for

each household, and for the community - The weight of each dimension of a given household is a

function of the summation of the impact area scores in that dimension. All the impact scores for

the impact areas defining each dimension are aggregated. Then the total score is computed by

aggregating the scores for all the five dimensions per household. The HVI is then computed by

dividing the calculated total scores per household with the total possible score when there is full

impact which was set at 100.

Draft

Chapter 4: HVI Methodology

4.1 HVI Data Requirements

Data required for HVI computation is no more than most data that is collected in baseline or

impact surveys by development organizations and governments through its different

departments. This data can be classified as primary and or secondary data.

a) Primary Data for HVI Computation

Most data used in HVI generation is regarded as primary data which should be collected on a

regular basis. This data is mostly on the livelihoods of households and communities under

investigation. For example during the development of the model, data used was largely drawn

from that collected in the 2004 FANRPAN study focusing on the identified 15 impact areas as

shown in the table below. The table also shows corresponding indicators that were tracked for

each impact area and used in HVI computation. A closer look at this table shows that most

organizations already collect most of the information used in the computation of the HVI.

Impact areas and variables to be used to measure household vulnerability

Impact areas Indicators

1 Optimal farm-household production decisions

% cash cropping Changes in input use (especially fertilizer)

2 Changes in household demographic structure and labour availability

household size dependency ratio No sick members

3 Changes in household productive physical capital assets

farm implements number livestock index

4 Sustainability of household food and nutrition security (food accessibility and utilization)

Number of meals per day Regular household income Household nutrition diversity Number of regular food sources

5 Impact on household Market Access

Net revenue from asset transactions Net revenue from crop transaction Distance from nearest market place

6 Agricultural extension services Access to extension services Absenteeism from extension meetings

7 Changes in household income and expenditure patterns

% expenditure on health care % expenditure on food

8 Changes in household productive financial capital assets

Savings withdrawals and deposits made Amount of credits received and level of interests charged

9 Impact on household investment choices

Farm equipment purchases and sales Livestock purchases and sales Land purchases/improvements Types of crops grown

Draft

10 Access to behavioral change information

Sources and quality of information on HIV and AIDS Sources and quality of information on agriculture

11 Changes in household productive natural capital assets

Access to land % land utilization

12 Mobility of household members Household disintegration due to HIV and AIDS

13 Gender implications % of female-headed households % of child-headed households

14 Support networks

Number and type of support from government, NGOs and local community Remittances from relatives Number of social networks

15 Environmental degradation Use of forest products Household access to water resources

However most important is the fact that the design of the HVI approach allows for flexibility in

the type of indicators used in the computations. The methodology allows for the use of different

indicators depending on the scope of the assessment. Thus data on new questions can be

collected and used in HVI analysis.

Generic HVI questionnaire (Annex 2) - Data for HVI computations is mostly collected

through semi-structured interviews with respective households. There already exists a generic

questionnaire and as indicated in the section above the questionnaire collects information on

basic livelihood of a household focusing mainly on the five livelihood assets. The questionnaire is

4 pages long and can be administered at most in 30 minutes. It is divided into 7 sections as

follows:

A. Household data - This section collects information on household demographics such as age,

gender, education, health, migration, etc.

B. Asset ownership – Collects information on physical and financial assets with the household such

as land, inventory e.g. fertilizer and seeds, quantity of food available, farm implements,

infrastructure e.g. water source, livestock assets, etc

C. Use and management of the environment – Collects information on use and management of natural

resources and the environment by the household.

D. Use of financial resources – Collects information on the use of financial resources within the

household

E. Household nutrition diversity – Information is related to food diversity within the household.

Usually the recall period for this section ranges from 1-7 days before the survey.

F. Sources and quality of information on HIV and AIDS – This collects information related to

household sources of information on HIV and AIDS

Draft

G. Social support networks – Information in this section is related to household’s access to social

support systems in their community

b) Secondary Data

Secondary data sources are also important when using the HVI approach. Information about the

communities where the study will be conducted is very important in HVI computation.

Secondary sources will mainly provide information regarding rainfall patterns, soil quality, prices,

etc. Although this information is not collected regularly, it should be updated every season.

There already exists a semi structured questionnaire for collecting community related information

that can be administered in less than 15 minutes.

4.2 HVI Database

The HVI has been built into a programmed database which allows HVI generation on a click of a

button. The database is user friendly and comes with a manual that users can refer to whenever

they have issues they want to clarify. Currently the HVI database is a Microsoft Access database

with SQL properties that allow for stability and handling of large records of data.

The HVI database has two interfaces i.e., the user interface that allows for viewing of existing

data and has provisions for data entry, view and print HVI and other reports such as distribution

lists, etc . The other interface is for administrative purposes. It allows a user with administrative

rights to basically manage the database i.e., to change certain factors within the HVI programme,

add or delete users, set user rights, process and update the HVI.

4.3 HVI Web Portal

FANRPAN has established an HVI web portal which acts as an online resource allowing

stakeholders to interact with each other on the HVI through the use of a discussion an e-forum.

The portal is a centralized facility that people can access from anywhere in the world whenever

they have access to the internet. The HVI web portal can be accessed on the following link

http://www.developmentdata.info/fanrpan/hvi.

Through the web portal stakeholders interested in the HVI can get regular updates about the

HVI through automated emails. The portal has provisions that allow stakeholders to subscribe to

a mailing list to allow them to receive the updates. The HVI website offers an online resource for

access to background information and development process of the HVI. Some published

reports on the HVI including workshop proceedings can also be posted on the website for easy

access by those interested. There also exist a comprehensive search facility to allow easy access to

information and documents.

Draft

Most importantly the HVI website has provisions for online computation of the HVI by

stakeholders. There is an online form provided on the website and thus by completing this form

and submitting their details, stakeholders can view their HVI online on a click of a button.

Draft

Chapter 5: Pilot Testing of the HVI

5.1 Pilot Testing of the HVI

Pilot testing of the HVI was conducted in Lesotho, Swaziland and Zimbabwe. The major

objective of this exercise was to access the applicability of the HVI under different conditions

and compare how the index would perform compared to traditional vulnerability assessment

methods.

A total of 460 households were interviewed and data analyzed using the HVI model. In

Zimbabwe the pilot test was conducted on an on-going HBC programme in Marange and Seke

communities. Affected and less affected households were defined by programme managers as

those with and without a person living openly with HIV respectively, plus those with orphans.

The study aimed at a 50:50 ratio of “affected” and “less affected” households. The survey was

successful in achieving this target. A total of 235 households were sampled. Affected and less

affected households were defined by programme managers as those with individuals openly living

with HIV and or AIDS and those with orphans. Approximately 49.8% of the households in the

sample were characterized as HIV and AIDS affected, while 50.2% of the households are less

affected by the pandemic (Fig 3).

Fig 3: Distribution of affected and less affected households by district

A vulnerability analysis was conducted on data collected in the two districts. Results in table

below show that approximately 51.3% of households in Seke district were at the coping level,

while 48.7% fell in the acute level of vulnerability. In Marange district, 29.5% of sampled

households were in the coping level, while 70.5% were in the acute level of vulnerability.

However, there were no households lying in the emergency level in both districts. On average,

49.2%

49.4%

49.6%

49.8%

50.0%

50.2%

50.4%

 Seke Mutare  Total

Affected

Less Affected

Draft

most of the households in the survey sample fell under the acute level of vulnerability i.e. 60% of

the households, while 40% are classified as coping.

Model Parameters used in Zimbabwe

HVI Level HVI Range Situation of households

Seke Marange Total

Vulnerability Level 1 HVI =<0.5 Coping level 58

(51.3%) 36

(29.5%) 94

(40%)

Vulnerability Level 2 0.5<HVI<0.75 Acute Level 55

(48.7%) 86

(70.5%) 141

(60%)

Vulnerability Level 3 HVI => 0.75 Emergency Level

0 0 0

Total (n) 113 122 235

However further analysis showed that it is possible to use the HVI to analyze inclusion and

exclusion errors in programming. This is particularly important in light of livelihood and

development interventions. Fig 4 below show that there were some households that were

included in both the HBC programmes in Marange and Seke communities yet their vulnerabilities

show that they should not have been included. They are also some households that were

excluded from the programme yet they were most deserving.

Fig 4: Exclusion and Inclusion Errors in studied HBC programming

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0 1 2 3

1=affected 2=less affected

HV

I

Coping level

HHds

Acute level

HHds

Emergency Level

HHds

These households were included but should not

These households were excluded but should be included

Draft

Results from the analysis also managed to show that it is possible to use the HVI analysis to

compare vulnerability levels across households, interventions, communities, regions and even

countries (Fig 5). This is particularly important in vulnerability assessments.

Fig 5a: Marange District Fig 5b: Seke District

5.2 Issues to be addressed in order to reduce vulnerability

The pilot testing also gave insights of issues that need to be addressed in order to reduce

vulnerability of households to the impacts of HIV and AIDS on agriculture and food security. In

light of the adverse impacts of HIV and AIDS on household assets, households need to manage

their assets efficiently so as to reduce their vulnerability levels. In addition to efficient

management of assets, households must be able to protect their asset base. This include

improved community based natural resources management, transfers of improved mechanisms

for resource protection and management, and mitigation measures for protection from risks.

Protection of human capital would focus on health and nutrition through provision of health

services. Ensuring access to micro credit such that the borrower is not made vulnerable by

indebtedness can protect financial assets.

In addition policies to expand asset base of the vulnerable are necessary. For example, land

reform where distribution of land is inequitable and granting of tenure rights to groups squatting

on public lands in urban areas or provision of credit loans to squatters to help them own the land

that they live on. Human capital can also be improved though provision of free or subsidized

education and health services as well as by ensuring sufficient levels of food and nutrition.

No. of house

hold

s

.75.69.63.56.50.44.38.31.25

50

40

30

20

10

0

Std. Dev = .08

Mean = .53

N = 122.00

Household Vulnerability indices

No. of house

hold

s

.75.70.65.60.55.50.45.40.35.30

40

30

20

10

0

Std. Dev = .08

Mean = .49

N = 113.00

Household Vulnerability indices

Draft

The quality of the expanded asset base is important to ensure the resilience of a community once

relieved of their vulnerability. Hence there is need to improve the quality of the expanded asset

base. Natural assets such as land have to be made more productive through provision of

agricultural extension services in rural areas and skills training in urban areas for home-based

activities. Physical infrastructure is best maintained when the community co-invests in its

provision and maintains the facilities by themselves.

5.3 Major Findings and Recommendations from Pilot Testing

The pilot testing produced the following major findings:

HVI proposes a new and robust way of tracking and analyzing vulnerability. However

adapting the model for wider community participation and a cost benefit analysis for

adopting the methodology in a programme is necessary.

The flexibility within the methodology allows for equitable use of limited resources by

beginning at the tail end of vulnerable households, i.e., with the most vulnerable.

The following conclusions and recommendations were drawn from the pilot testing:

a) Policymakers and development specialists can use the HVI to design, plan and

implement comprehensive and well targeted public funded social protection

programmes that specifically reduce household vulnerability and improve food security

among HIV affected families.

b) There is potential value addition from further research to provide practical solutions to

developmental problems. Researchers working on different areas such as HIV and

AIDS, agriculture, food security, and health can utilize the model to come up with

practical solutions in their studies. Such research could also help improve on the model

which will be a positive development.

c) The model will not be useful without support from policymakers in the SADC region

and funding partners who provide the financial resources for its application. Efforts

should be made to ensure that there is a continued dialogue especially with the

responsible policymakers so that there is unwavering government support in the

promotion of the model in government and other development partners’ programmes.

d) There is a genuine need to build upon existing opportunities to form strategic

partnership with organizations willing to take the HVI to another level. This will help

promote the wide use of the HVI in the development community. The partnerships will

provide an opportunity to apply the HVI on a wider spectrum and maybe in different

environments. This is important as it then assists in evaluating the universality of the

model.

Draft

e) A major challenge is to target the benefits of social protection transfers to the most

needy – especially in the context of HIV and AIDS. Vulnerability should not be used

synonymously with need as it should reflect the likelihood of a particular outcome

arising for a defined group in the future.

f) There is need to operationalize the HVI within the context of work conducted by

development oriented organizations. Such an opportunity will ensure further evaluation

of the model and customization and development of an operational guideline on how to

apply the HVI in development work.

Draft

Chapter 5: Application of the HVI

5.1 Where is the HVI applicable?

The HVI is applicable in development work meant to improve social protection systems for the

poor and most vulnerable groups in African societies. FANRPAN believes the HVI can be

applied in programming and targeting of development interventions, vulnerability assessments

and monitoring and evaluation of development programmes.

5.1.1 Programming and targeting- The HVI is expected to improve targeting of food

aid and other development interventions. The HVI improves programming and

targeting of mitigation responses in three ways:

It makes it possible to classify households according to their level of

vulnerability thereby allowing the targeting of the most affected households

first. This is particularly important where they are limited resources available for

interventions.

It makes it possible to identify the source of vulnerability within a household’s

livelihood thereby making it possible to come up with specific intervention

programmes targeted at addressing these problems. Where a relief agency has a

package of interventions e.g. for food distribution, income generation or

agriculture production, it is possible to use the HVI to allocate which

households qualify for which intervention, within the same community. It is also

possible during implementation to then check if a household has graduated

from a given level of vulnerability and thus no longer qualify for that particular

intervention, and assign it to another intervention if available. The reverse it

also true. The HVI makes it possible for relief agencies and development

organizations to start from the communities and then design appropriate

programmes that suit community and household needs.

The HVI makes management of programmes easier and enjoyable. The

approach makes it possible to deal with pipeline breaks that are always

happening in programming by providing an objective way of scaling up and

down of programmes. If operational research proves the HVI to be an

acceptable measure of vulnerability by communities then the approach has the

potential to reduce social tensions that are a result of these pipeline breaks.

Draft

5.1.2 Vulnerability Assessments –Use of HVI will improve vulnerability assessments in

the SADC region and beyond. Previously, vulnerability assessments have not been

quantitative and therefore made effective targeting of interventions difficult.

Therefore the HVI offers an opportunity for quantitative inclusion of HIV and

AIDS and other vulnerability shocks into regional vulnerability assessments

conducted by Vulnerability Assessment Committees (VACs). Categorising

household vulnerability is important as households affected by HIV and AIDS are

not at the same level of need, neither is that need synonymous with vulnerability.

Empirical evidence shows that not all HIV-affected households are food insecure

and that many unaffected households are actually food insecure. This runs contrary

to generalised labelling of AIDS-affected households as vulnerable and in need of

food security.

5.1.3 Monitoring and Evaluation – The HVI will make monitoring and evaluation of

development interventions easier. With the growing call for accountability given

limited food and financial resources there is a need to demonstrate how resources

have been used and what impact they had on the lives of the target population. The

HVI approach makes it possible to track improvements in the lives of the affected

communities as a result of the intervention. Furthermore when HVI data is collected

over time using prescribed methods, it is possible to compare across communities

and check the trends over time. This is important to track the effect of any

interventions in the region.

Draft

Chapter 6: Reception of the HVI in the SADC Region

6.1 Introduction of HVI to regional development partners

The HVI concept was introduced to development partners in the region through various forums

such as the Agricultural Coordination Working Group convened by FAO in Zimbabwe and

Vulnerability Assessment Committees in Lesotho and Swaziland. A regional workshop on the

HVI was held on the 4th of September 2008 in Zambia and was attended by more that 200

participants from across Africa and beyond. The general consensus among stakeholders was that

the HVI had potential to be a useful development model. Most civil society organizations

including UN agencies felt that the HVI offered an opportunity for improving targeting of

interventions meant to reduce the impacts of HIV and AIDS on the rural society. The Zimbabwe

Vulnerability Assessment Committee, for example, felt that the index could go a long way in

improving the quality of vulnerability assessments. In the initial stages some organizations such

as Food Security Network of Zimbabwe (FOSENET), World Vision, World Food Programme

(WFP), and Food and Agriculture Organization (FAO) indicated their willingness to put the HVI

to test within their programmes.

6.2 HVI Regional Policy Dialogue Workshop

As indicated in Section 6.1 the regional workshop was held in Zambia from the 4th to the 6th of

September 2007. The theme for the workshop was Policy “Triggers” for Agricultural Growth in

Southern Africa. The workshop had two main purposes: 1) to share major findings and policy

recommendations emerging from recent research in Lesotho, Swaziland and Zimbabwe on the

impact of HIV and AIDS on Food Security in Southern Africa and how the Household

Vulnerability Index (HVI) can be used to shed light on the different degrees and levels of

household vulnerability introduced by the pandemic and 2) to obtain recommendations for

future work in this area by FANRPAN.

Several emerging policy issues around research on the impacts of HIV and AIDS on agriculture

and how the HVI can be utilized in this context were proposed. These were as follows:

Policy makers and development planners can use HVI to design and implement targeted

interventions: The current challenge is to develop the framework on how this can be

applied

Funding for the integration of HVI into new and existing interventions is required. The

identified need for operational research on the HVI requires resources for the

implementation.

Draft

HVI should be packaged for three identified groups of end users of the tool in the

region. These groups are individual researchers, civil society organizations and

international agencies.

The workshop concluded that further operational research and wider application of the

methodology in at least three countries should be done in order to ensure that all the operational

constraints of using the HVI are dealt with in preparing of a wider rollout of the tool.

FANRPAN was also tasked with spearheading a regional adoption and implementation plan for

the HVI. This will then form the foundation upon which further work on the HVI in the region

will be based. This adoption and implementation plan should have time frames which will guide

activities and the achievement of set objectives.

6.3 Use of the HVI by FOSENET and World Vision International

Although a number of organizations have shown interest in the HVI only two have taken it upon

themselves to put the HVI to test. These are the Food Security Network of Zimbabwe and

World Vision International. These organizations in partnership with FANRPAN availed some

resources for use and operationalising of the HVI within their context.

a) Food Security Network of Zimbabwe (FOSENET)

They were the first organization to put the HVI to test in 2007. FOSENET commissioned a

study for assessing the impacts of HIV and AIDS on agriculture and food security in two

districts in Zimbabwe, using the HVI model with a view of coming up with intervention

strategies that best suit these two districts. Results from this showed that the HVI was able to

quantify vulnerability of studied households with relative accuracy of 80-90% when compared

with other methods such as community ranking. Were deviations were found these were mainly

due to errors in data collection and misrepresentation of information. The study was able to

categorize households into three levels of vulnerability and proposed interventions were derived

from the HVI analysis.

b) World Vision International

In March 2008 World Vision International commissioned an operational research in Swaziland,

Lesotho and Zimbabwe meant to use and evaluate the applicability of the HVI in its food

transfer programmes. The study aims at developing an information management system for

programme implementation in the pilot sites; and determining the HVI’s effectiveness in

identifying the most vulnerable households appropriate for a specific intervention. The specific

objectives are to assess the effectiveness of the HVI as a targeting/ management tool in dealing

with pipeline breaks and project transition i.e. scaling down, up or changing intervention types; to

determine the cost effectiveness of using the HVI relative to the current practice of targeting; to

Draft

determine the appropriate frequency of updating information in order to avoid inclusion and

exclusion errors in programmes; and to assess the level of acceptability and satisfaction of the

HVI as an objective targeting tool by both communities and field staff.

The operational research is longitudinal study spanning a minimum of two years; the study covers

a minimum of one WV operational Area Development Programme in each of the study

countries. The study is divided into two phases with the first phase being a systematic effort to

develop data collection and management systems for the selected areas. The second phase then

focuses on critical factors for continued use of the HVI, i.e. the frequency of updating

information which is intricately connected to the cost. WV as an organization seeks to empower

communities; as such it endeavours to have effective community participation in the refinement

of the HVI.

6.4 Other partners in the SADC region that would find the HVI useful

Several other partners in the SADC region could find the HVI useful in their programmes. These

include:

Non Governmental Organizations (NGO) implementing impact mitigation programmes but not using

a universally acceptable approach to targeting and monitoring of their programmes could use the

HVI for targeting, monitoring and evaluation. The HVI provides a basis upon which

organizations can effectively target and monitor the effectiveness of those programmes. The

model also provides an efficient way of deriving appropriate response packages for identified

vulnerable communities.

Famine Early Warning Systems Network (FEWSNET) – This is an international network whose

mandate is to strengthen the abilities of African countries and regional organizations to manage

risk of food insecurity through the provision of timely and analytical early warning and

vulnerability information. The network uses the livelihood framework to food security analysis. It

is in this analysis where FEWSNET can integrate the HVI to come up with refined results that

efficiently identify food secure and insecure households, zones, countries or regions. This is

important for decision making especially emergency relief planning purposes.

Regional Vulnerability Action Committee (RVAC) - these committees are responsible for conducting

vulnerability assessment in all the SADC countries. Of late there has been a disgruntlement from

the civil society organizations in the region on the lack of a significant consideration of HIV and

AIDS as a factor that affects food security. The HVI provides a method by which the RVAC

could quantitatively include impacts of HIV and AIDS in its analysis. In this way the RVAC

would be able to determine the extent to which HIV and AIDS is affecting food security in the

SADC region.

Draft

Annex 1: VARIABLE TRANSFORMATION PROCESS

Dimension Hypothesis tested Variables for testing hypothesis Transformation

Natural Capital

Soil fertility declines for vulnerable households as application of natural fertilizers declines.

Proportion of field fertilized by natural means. What proportion X of the fields is fertilized by natural means?

2X; CLH:50-100%=0, ALH:0-50%=1,ELH:none=2

Barriers to access to land for agriculture increase vulnerability

Barred from use of land that you used to cultivate No=0 Yes =1

Households revert to the environment for "free" products such as wood when vulnerable. HIV and AIDS affected households rely more on the forest for their livelihoods.

Tree cutting or wood selling as a means of survival, wild fruits collection, environmental management in the presence of sickness or death, quality of water used by household, participation in water or environmental management

2X/5; CLH:answer yes to at most 1 question=0; ALH:answer yes to 1-3 environment questions=1; ELH:answer yes to at least 4 environment questions

Affected households have difficulties in fully utilizing their land due to limited labour and draft power availability. Vulnerable households do not fully utilize their existing land

% of land not utilized due to sickness (X) What is the total land under cultivation (A)? What land is available but not cultivated due to illness or death in the last season (B) ?

X=B/(A+B) 0% =0 CLH:0-20%=1 ALH:20-50%=3 ELH:>50%=5

Human Capital

Affected households are vulnerable when they have sick members, and the more the number of sick members, the more the vulnerability. Also worse if the sick member is the head of the household.

Proportion of sick members (X). What is the total Household size (Y)? How many members are sick regularly (have been bedridden for at least three different times in the last year, with each bout extending to up to a week? Or have been diagnosed with any of TB, Meningitis, Caporsi Sarcoma, Hepatitis, Pneumonia (Z)?)

X=Z/Y

Households that have productive sick members are more vulnerable.

Who is regularly sick None=0 dependent =1 productive adult = 2 Spouse=3 HH head = 4

Highest possible score

Affected households have a greater number of dependents due to the increasing number of orphans in such households

Dependency ratio (economic burden)X :Number of dependants ({0-15}+{>65} +{bedridden or disabled})/Number of economically active.

Modified dependency ratio: X=dependants/total HH size. CLH: X<0.4; ALH: 0.4<X<0.75 ; ELH: X>0.75

Female headed and/or child headed households are less able to cope with shocks, compared to male headed households

Age and gender of household head CLH=0 ALH=3 ELH=6

HIV and AIDS has caused disintegration in affected households

Household members who have moved away due to sickness or death

CLH: 0; ALH:2 CLH: 2

Physical Capital

Vulnerability especially to food insecurity increases with less use of fertilizers

Nitrogen fertilizer use for staple crop(X). What is your land size Y in ha? What is the weight Z of top dressing fertilizer used in the last season in Kg?

X=Z/400Y CLH:X>0.5; ALH:0.25<X<0.5; ELH: X<0.25

Affected households have reduced harvests due to limited labour and draft power

Staple cereal output per capita (X). What is the total household size (Y)? How kgs of Maize were harvested (Z)? X=Z/Y

X=Z/150Y CLH:X>0.5; ALH:0.25<X<0.5; ELH: X<0.25

Households that do not own an ox drawn plough or cart are likely to face difficulties in cultivation, planting and other farming operations.

Ownership of a plough or ox drawn cart Owns a plough and cart = 0, plough only = 1 cart only =2 none =3

Draft

Households that do not own or own fewer cattle and other livestock are more vulnerable due to limited access to draft power and alternative sources of income and nutritious food.

Productive livestock index X = 3c+ G+S+2D. How many Cattle do you own (C)? Goats (G)? Sheep (S)? Donkeys (D)?

CLH: X>6; ALH: 6>X.>3; ELH: 3>X

Affected households adopt unsustainable short term coping strategies which might include the selling of assets such as livestock and farm

Livestock sales index X = (3c+g+s+2d)/(3C+ G+S+2D) How many Cattle do you own (C)? Goats (G)? Sheep (S)? Donkeys (D)? How many Z (=3c+g+s+2d) of each were sold in the last year?

CLH: X<0.2; ALH: 0.2<X<0.5; ELH: X >0.5

Affected households have limited access to extension services due to ill health and inadequate time to devote to such activities.

Access to extension services

Used both = 0; used crop only = 1Used livestock only = 2; do not even know = 3

Financial

Households with little or no savings are more vulnerable

Reliance on bank savings

Every month = 0 In crises only = 1 Do not have many in the bank anymore=2 Do not own a bank account =3

Affected households have fewer sources of regular income due to unavailability or limited number of formally employed members in a household

Regular sources of financial resources Salary (S), Crop Sales (Cs); Livestock Sales (Ls); Remittance from HH member (Rm), No regular source (Ns)

S=0; Rm=1 Cs=2; Ls=1; Ns=3

Affected households have limited access to credit loans due to increased risks and lack of collateral associated with such households

Access to credit loans

Household is part of a community or formal credit scheme= 0 borrow from extended family/neighbour = 1 no access to credit loans at all = 3,

Households with unpaid debts are most vulnerable.

Presence of unpaid debts No=0, Yes= 3

Affected households experience increased expenditure on health care due to the presence of more ill members in the household

Expenditure patterns. Food (F), Non-food basic goods (nF), Health (H), Savings (S), Transport to Clinics (Tc), Transport to Work (Tw), Farming inputs/implements (FI), Do not prioritize/plan (Nm) Other (o) , Beer and recreation (B), School Fees (SF),

FI/S/o=0, Tw/B/SF/F/nF=1, H/Tc/=2, Nm=1

Use of additional resources indicate choices under vulnerability

Expenditure of additional financial resources Food (F), Non-food basic goods (nF), Health (H), Savings (S), Transport to Clinics (Tc), Transport to Work Tw), Farming inputs/implements (FI), Other (o) , Beer and recreation (B), School Fees (SF), Income generating projects (Pr)

FI/Tw/o/B/S/Pr=0, Tw/nF=1, Tc/SF=1, F/H=2

Purpose for selling harvests indicates levels of vulnerability.

Use of revenue from crop sales Food (F), Non-food basic goods (nF), Health (H), Savings (S), Transport to Clinics (Tc), Transport to Work (Tw), Farming inputs including Veterinary (FI), Do not get enough to sell (Nm) Other (o) , Beer and recreation (B), School Fees (SF), Income generating

FI/S/o=0, Tw/B/SF/F/nF=1, Tc/=1, H/Nm=2

Affected households eat less per day due to inadequate food availability

Meals per day

Breakfast, Lunch, Dinner, give 0 for each taken ie 1 meal= 3, 2 meals=2; 3 meals=0;

Draft

Affected households eat less variety per day due to inadequate food availability

Describe the typical food stuffs in meals taken in your household? Maize (porridge/sadza/samp) (St), tea St, sorgum brew St, green vegetable V, wild fruit F, bananas/oranges/apple F, sugar cane St, pumkins V, groundnuts Pr sweet potatoes St, meat Pr, fish Pr,

Give 1 for each category taken, CLH:X>3 ALH: 2<x<3; ELH: X<2

Social Capital

The lesser the number and quality of support channels from external sources, the greater the vulnerability

What support was obtained from Government, NGOs, community and other external support networks in the last 3 months? Give the commonest 2. Food (F), Non-food basic goods (nF), Health (H), Savings (S), Transport to Clinics (Tc), Transport to Work (Tw), Farming inputs including Veterinary (FI), Do not get support(Ns) Other (o) , Beer and recreation (B), School Fees

Tc/H=0; Tw/B/SF/F/nF=1, FI/S/o=2, Ns=4

The lesser the volume of support from external sources the greater the vulnerability

In which areas did support from Government, NGOs, community and other external support networks completely meet households' requirements? Food (F), Health (H), Transport to Clinics (Tc), Farming inputs including Veterinary (FI), Do not get support(Ns) School Fees (SF),

none=2 ; F/H=1; else =2

The more informed a household is, the less vulnerable the household

1. Do you have adequate knowledge to cope with AIDS related illnesses for family members?, 2. Do you have adequate knowledge on type of crops to grow, and when to. 3. In any given season, do you know- in advance- the weather forecasts and use this forecasts

count of "No" answers

Draft

ANNEX 2: GENERIC HVI QUESTIONNAIRE

HOUSEHOLD DATA CARD

Date of data collection: _____/______/_________ Village: _________________________________ Name of respondent: ______________________________ Day / Month / Year

A. Household Data

Full Name National/WVI ID NO

(format: XX-XXXXXXX-X-XX)

Year of birth

Sex M or F

Education2 Employment3 Health4

1 HH Head

2

3

4

5

6

7

85

Record Household members that have relocated within the last three months

9

10

2 Illiterate=0, Some Primary School=1, Completed Primary School=2, Some Secondary School=3, Completed Basic Secondary School=4, Completed Advanced Secondary/Pre-University School=5, Professional College

certificate=6, University Education=7, Other = 8 3 Unemployed/Homemaker/NA=0, Subsistence farmer = 1, School child=2, Artisan/Skilled Tradesman/woman = 3, Petty Trade = 4, Formal Employment=5, Harvesting natural resources(wood, panning etc) 4 Good=0, Regularly (sick at least once every three months) Sick=1, Bedridden=2 Then record the sickness: good health=0, TB/neumonia/Kaposi/=1, Malaria=2, Headache/whole body=3, stomach ache=4 5 For household members exceeding 8, attach additional form.

Household Identification Number: _______/______/______/________/__________ Enumerator: ____________________________________ Country District ADP Village ID

Draft

11

Total in household:

Draft

B. Asset Ownership

Number/Size State6 Asset increased within the last year

Asset reduced within the last year

Land size in acres

Land area under staple crop in acres

Area under staple crop

Amount of fertilizer (AN) used for staple crop in kgs

Land areas forcibly taken from household (barred by relatives, the chief or other community members)

Staple crop available right now in kgs

Meals taken per day

Plough

Cattle

Goats

Donkeys

Sheep

Pigs

Chickens

Agriculture extension services for livestock

Agriculture extension services for crops

Bank account (approximate balance now)

Remittance

community or formal credit scheme

unpaid debt

extended family/neighbour support

Land (acres) fertilized by natural means in the past season

Land (acres) available but not cultivated due to illness or death in the last season?

Source of drinking water

Type of Latrine

C. Use and management of the environment Yes No

Have you ever resorted to cutting down trees and selling wood as a means of survival?

Have you ever resorted to collecting wild fruits because you do not have enough food for three meals a day?

6 Poor/need improvement=0, Satisfactory quality=0, Good=1, Don’t know=2

Draft

Has sickness or death of a family member prevented you from managing your environment e.g. gully filling, manure collection etc?

Has sickness or death affected the amount or quality of water used by your household? E.g. resorting to collecting water from nearer but unsafe sources or failing to pay for piped water or failing to pay for repairs to safe water sources?

Has sickness or death prevented your household from ever developing or participating in planned water or environmental management projects? E.g. borehole drilling, tree planting, participation in community initiatives?

D. Use of financial resources

Where does the HH spend most of its financial resources (give the most common)

Where would you spend any additional financial resources if they were availed to you: (give the most important)

For what purpose did the household use financial resources from sale of crops from the last season? (give the most important)

1= Food 2= Non –food basic goods 3= Health 4=Savings 5=Transport to work 6=Transport to clinics 7=Burial expenses 8=Farming inputs 9= Beer and recreation 10=School fees 11= IGP 12=other E. Household Nutrition Diversity Has household consumed food within the specified food group in the past week before the survey?

Food Group (1)Yes (2) No

Grains (maize, sorghum, millet, rice, wheat, etc)

Beverages (tea, etc)

Sugars and sugar cane

Oils (avocado pear, nuts and seeds, etc)

Vitamin C- rich vegetables e.g. spinach, green leaf vegetables, potatoes, cauliflower, cabbage

Tubers (potatoes, sweet potatoes, cassava, etc)

Meat bean and fish

Vitamin A – rich vegetables e.g. spinach, carrots, peas, pumpkins, sweet potatoes, squash, butternut

Eggs

Milk

Vitamin C- rich fruits e.g. mango, oranges, naarjties apples, guava, banana, lemon, peaches, avocado pear, tomatoes

Other fruits (include wild fruits)

Sorghum brew

Draft

F. Sources and Quality of Information on HIV and/or AIDS Yes No

Do you have adequate knowledge to cope with AIDS related illnesses for family members?

Do you have adequate knowledge on type of crops to grow, and when to.

In any given season, do you know- in advance- the weather forecasts and use this for farming planning?

Do you have access to projects or interventions that can raise income for your household?

G. Social support networks

Part A: Indicate the most useful support your HH got from government, NGO community or other external networks in the last 3 months by writing the appropriate type in the relevant box. (Choose from list below the table) Part B: In which areas did support from government, NGOs, community or other external networks completely meet your households’ requirements

Source of support

Government

NGO Community Other external support

Part A

Part B

1- Food 2- Non –food basic goods 3- Health Savings 4- Transport to work 5- Transport to clinics 6-Burial expenses 7- Farming inputs 8- Beer and recreation 9- School fees 10- IGP 11- Other