Presentation given in Sixth RENEWAL Regional Workshop: A decade of work on HIV, food and nutrition security. By Stuart Gillespie

1. HIV and Vulnerability
Stuart Gillespie
International Food Policy Research Institute
Regional Network on AIDS, Livelihoods and Food Security
Cape Town, 10 November 2010

2. Three stages of vulnerability
m id-stream
HIV AIDS
upstream downstream
Food insecurity
Malnutrition

3. The world of income
© Copyright 2006 SASI Group (University of Sheffield) and Mark Newman (University of Michigan).

4. The world of HIV
© Copyright 2006 SASI Group (University of Sheffield) and Mark Newman (University of Michigan).

6. “Is Poverty or Wealth Driving HIV Transmission?”
Gillespie, Kadiyala, Greener (2007)
AIDS, Vol. 21, Suppl. 7, S5-16
www.AIDSonline.com

7. Upstream vulnerability
HIV
Food insecurity
Malnutrition

8. Risk in southern Africa
• Unprotected sex
• Multiple, concurrent sexual partnerships
• Coexisting STIs
• Non-circumcision
• Early sexual debut
……but what underpins and drives these risk factors and
behaviors?

9. HIV and Poverty in Africa
25% Botswana
Lesotho
Zimbabwe
20% Namibia
South Africa
Southern Africa
R squared = 0.0996 Zambia
Mozambique
not significant
HIV Prevalence
15% Malawi
Central African Republic
10%
E&W Africa
Côte d'Ivoire
Tanzania R squared = 0.0307 Uganda
Kenya not significant
5% Cameroon
Nigeria
Rwanda Burundi
Ghana
Ethiopia Gambia Mali
Senegal Burkina Faso Sierra Leone Niger
Mauritania Madagascar
0%
0 10 20 30 40 50 60 70 80
Percentage below $1 per day

10. HIV and Income Inequality in Africa
35%
Swaziland
30%
R2 = 0.4881
p=0.005%
25% Botswana
Lesotho
HIV Prevalence
Zimbabwe Namibia
20%
South Africa
Zambia
Mozambique
15% Malawi
Central African Republic
10%
Tanzania Uganda Côte d'Ivoire
Kenya Cameroon
5% Rwanda Nigeria
Burundi
Ghana Mali
Ethiopia
Senegal Niger
0%
0.25 0.35 0.45 0.55 0.65 0.75
GINI Coefficient

11. Recent evidence (2005 -2008) from Africa
Data
– Cross-sectional cross country analyses (DHS)
– Longitudinal seroconversion studies
– Longitudinal household surveys
– Studies linking other interacting factors (mobility,
gender, malnutrition, comorbidities) with HIV risk
Outcomes
– High risk behaviors
– HIV prevalence (% of population estimated to be HIV +)
– HIV incidence (number of new infections/year)
– Prime age adult mortality (15-59 years of age)

12. Economic status and HIV prevalence
Cross-sectional data from 8 countries (Mishra et al 2007)
14.0
Highest, 11.9
12.0
Fourth, 10.5
10.0
Middle, 9.1
HIV Prevalence
Second, 8.2
8.0 Highest, 7.6
Fourth, 7.3
Middle, 6.9
Lowest, 5.9
6.0
Second, 5.1
Lowest, 4.8
4.0
2.0
0.0
Men Women
Asset quintiles
• Limitations:
– Simultaneous causality (Economic status HIV)
– Wealthier more likely to live longer ( HIV prev. among wealthy)

13. Factors predisposing wealthier groups to…
• Greater risk:
– More money
– Greater mobility
– More leisure time
– Earlier sexual debut
– More lifetime concurrent partners
– More likely to be urban-resident
– Greater alcohol consumption
– Better nourished (live longer)
– Better access to health care and ARV drugs
• Less risk
– Better nourished (less biological susceptibility?)
– Better access to health care (e.g. STI treatment)
– Better communications
– Better education
– Men more likely to be circumcised
– More likely to use a condom

14. Economic status, HIV incidence and adult mortality
• 3 prospective seroconversion studies
– Lowest male HIV incidence among wealthiest asset
tertile (Lopman et al, Manicaland)
– Lowest incidence in middle tertile (Barnighausen et al, KZN)
– No association (Hargreaves et al, Limpopo)
– Limitation: High attrition rates
• Rural household panel data (MSU and Kadiyala)
– In Kenya and Zambia, asset non-poor men more likely
to die in prime age
– In Ethiopia, poor men more likely to die in prime age

15. Role of other socioeconomic factors
• Education increasingly associated with less risky
behaviors and lower HIV incidence (Hargreaves et al 2008)
• Gender, age and economic asymmetries Positively
• Food insecurity (among women) associated
• Low social cohesion (e.g. slums) with HIV +ve
status
• Mobility (“Rhodes not roads”)
• Women engaged in some form of self-employment less
likely to die in prime age (MSU and Kadiyala)

16. Conclusions
Pathways and interactions are complex.
Relationships are dynamic and may change over time
Upstream
• “Poverty” is not the predominant driver of HIV transmission in most
contexts in southern Africa
• Inequalities (gender, economic, age) are important
• “Food insecure” women are also particularly vulnerable
• Social cohesion and individual hope are under-researched
Midstream
• Malnutrition and coexisting STIs
Downstream
• AIDS impoverishes households, but depends on configuration of assets
and capabilities
• Women and children particularly affected