HIV and Vulnerability


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

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HIV and Vulnerability

  1. 1. HIV and Vulnerability Stuart Gillespie International Food Policy Research InstituteRegional Network on AIDS, Livelihoods and Food Security Cape Town, 10 November 2010
  2. 2. Three stages of vulnerability m id-stream HIV AIDSupstream downstream Food insecurity Malnutrition
  3. 3. The world of income© Copyright 2006 SASI Group (University of Sheffield) and Mark Newman (University of Michigan).
  4. 4. The world of HIV© Copyright 2006 SASI Group (University of Sheffield) and Mark Newman (University of Michigan).
  5. 5. “Is Poverty or Wealth Driving HIV Transmission?” Gillespie, Kadiyala, Greener (2007) AIDS, Vol. 21, Suppl. 7, S5-16
  6. 6. Upstream vulnerability HIV Food insecurity Malnutrition
  7. 7. 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?
  8. 8. HIV and Poverty in Africa 25% Botswana Lesotho Zimbabwe 20% Namibia South Africa Southern Africa R squared = 0.0996 Zambia Mozambique not significantHIV Prevalence 15% Malawi Central African Republic 10% E&W Africa Côte dIvoire 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
  9. 9. HIV and Income Inequality in Africa 35% Swaziland 30% R2 = 0.4881 p=0.005% 25% Botswana LesothoHIV Prevalence Zimbabwe Namibia 20% South Africa Zambia Mozambique 15% Malawi Central African Republic 10% Tanzania Uganda Côte dIvoire 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
  10. 10. Recent evidence (2005 -2008) from AfricaData – Cross-sectional cross country analyses (DHS) – Longitudinal seroconversion studies – Longitudinal household surveys – Studies linking other interacting factors (mobility, gender, malnutrition, comorbidities) with HIV riskOutcomes – 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)
  11. 11. 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, 9.1HIV 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)
  12. 12. 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
  13. 13. 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
  14. 14. 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)
  15. 15. ConclusionsPathways and interactions are complex.Relationships are dynamic and may change over timeUpstream• “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