hiv and vulnerability
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HIV and Vulnerability
Stuart GillespieInternational Food Policy Research Institute
Regional Network on AIDS, Livelihoods and Food Security
Cape Town, 10 November 2010
HIV AIDS
upstream downstream
Food insecurity Malnutrition
mid-stream
Three stages of vulnerability
The world of income
© Copyright 2006 SASI Group (University of Sheffield) and Mark Newman (University of Michigan).
The world of HIV
© Copyright 2006 SASI Group (University of Sheffield) and Mark Newman (University of Michigan).
“Is Poverty or Wealth Driving HIV Transmission?”
Gillespie, Kadiyala, Greener (2007)AIDS, Vol. 21, Suppl. 7, S5-16
www.AIDSonline.com
HIV
Food insecurity Malnutrition
Upstream vulnerability
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?
HIV and Poverty in Africa
0%
5%
10%
15%
20%
25%
0 10 20 30 40 50 60 70 80Percentage below $1 per day
HIV
Pre
vale
nce
BotswanaLesotho
NamibiaZimbabwe
Zambia
Malawi
Mozambique
Sierra Leone
Tanzania
Central African Republic
Ethiopia
Côte d'Ivoire Uganda
Kenya
Rwanda
South Africa
Mali
NigeriaCameroon
NigerMadagascar
GambiaBurundi
Ghana
Burkina FasoSenegalMauritania
Southern AfricaR squared = 0.0996not significant
E&W AfricaR squared = 0.0307not significant
HIV and Income Inequality in Africa
R2 = 0.4881p=0.005%
0%
5%
10%
15%
20%
25%
30%
35%
0.25 0.35 0.45 0.55 0.65 0.75GINI Coefficient
HIV
Pre
vale
nce
Botswana
Lesotho
NamibiaZimbabwe
Zambia
Malawi
Mozambique
Tanzania
Central African Republic
Ethiopia
Côte d'IvoireUgandaKenya
Rwanda
South Africa
Mali
NigeriaCameroon
Niger
BurundiGhana
Senegal
Swaziland
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)
Economic status and HIV prevalence
• Limitations:– Simultaneous causality (Economic status HIV)– Wealthier more likely to live longer ( HIV prev. among wealthy)
Cross-sectional data from 8 countries (Mishra et al 2007)
Lowest, 4.8
Lowest, 5.9
Second, 5.1
Second, 8.2
Middle, 6.9
Middle, 9.1
Fourth, 7.3
Fourth, 10.5
Highest, 7.6
Highest, 11.9
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
Men Women
HIV
Prev
alen
ce
Asset quintiles
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
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
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 • Food insecurity (among women)
• Low social cohesion (e.g. slums)
• Mobility (“Rhodes not roads”)
• Women engaged in some form of self-employment less likely to die in prime age (MSU and Kadiyala)
Positively associated with HIV +ve status
ConclusionsPathways 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-researchedMidstream• Malnutrition and coexisting STIsDownstream• AIDS impoverishes households, but depends on configuration of assets
and capabilities• Women and children particularly affected
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