HIV and development challenges for Africa Catherine Hankins, Associate Director & Chief Scientific Adviser to UNAIDS

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Catherine, Associate Director & Chief Scientific Adviser to Session: Challenges of globalisation, regional integration and development of Africa 10 th Anniversary of the Centre for the Study of Globalisation and Regionalisation Centre at Warwick University Warwick, September 17, 25 October,

There is no one African epidemic: know your epidemic and act on it Upstream effects: structural drivers in Africa: poverty versus income equality: which is more powerful? Downstream impact: long wave impacts on poverty, GDP, human capital, social capital Responding to the interaction between HIV and poverty

Estimated number of people living with HIV and adult HIV prevalence Global HIV epidemic, 1990 2005* HIV epidemic in sub-saharan Africa, 1985 2005* Number of people living with HIV (millions) % HIV prevalence, adult (15 49) Number of people living with HIV (millions) % HIV prevalence, adult (15 49) 50 5.0 30 15.0 40 4.0 25 12.5 30 20 3.0 2.0 20 15 10 10.0 7.5 5.0 10 1.0 5 2.5 0 1990 1995 2000 2005 0.0 0 1985 1990 1995 2000 2005 0.0 Number of people living with HIV % HIV prevalence, adult (15-49) This bar indicates the range around the estimate *Even though the HIV prevalence rates have stabilized in sub-saharan Africa, the actual number of people infected continues to grow because of population growth. Applying the same prevalence rate to a growing population will result in increasing numbers of people living with HIV. 2.2

Percent of adults (15+) living with HIV who are female, 1990 2006 Percent Female (%) 70 60 50 40 30 20 10 Sub-Saharan Africa Caribbean GLOBAL Latin America E Europe and C Asia Asia 0 1990 1992 1994 1996 1998 2000 2002 2004 2006 Figure 1

HIV prevalence (%) in adults in Africa, 2005 2.5

HIV prevalence (%) by gender and urban/rural residence, selected sub-saharan African countries, 2001 2005 2005 30 15 49 years old, by gender % 20 10 0 Women Men 15 24 years old, by gender % 30 20 10 Women Men 0 15 49 years old, by urban/ rural residence % 30 20 10 0 Lesotho South Africa Zambia Kenya Uganda UR Tanzania Burkina Faso Urban Rural Ghana Guinea Senegal South East West Sources: Demographic and Health Survey reports (Lesotho, Zambia, Kenya, Burkina Faso, Ghana, Guinea and Senegal) (2001 2005). Nelson Mandela Foundation (South Africa) (2005). Ministry of Health (Uganda). Tanzania Commission for AIDS (UR Tanzania) (2005). 2.7

Illustrative Results Resources Needed for Prevention Univ Precautions Male circumcision Safe injections Millions of US$ 16,000 14,000 12,000 10,000 8,000 6,000 4,000 2,000 0 2006 2010 2015 PEP Blood safety PMTCT STI treatment Condoms Social marketing Other vuln. pops. Prevention for PLHA Workplace IDU MSM CSW Youth out of school Youth in school VCT Comm. Mobilization Mass media Targets reached in 2010

Disconnect between dynamics of the epidemic and action: example from a West African country General population prevalence 1.8%; antenatal clinic data stable 10 years Peak age is 35-39 years (low prevalence in youth) Sex worker HIV prevalence 78% and 82% in 2 largest cities 75% of new infections in men in the capital city are clients of sex workers Strategic plan presupposes a highly generalised epidemic with widest possible engagement of society and a broad range of interventions Only 0.8% of AIDS investments are focused on sex work

There is no one African epidemic: know your epidemic and act on it Upstream effects: structural drivers in Africa: poverty versus income equality: which is more powerful? Downstream impact: long wave impacts on poverty, GDP, human capital, social capital Responding to the interaction between HIV and poverty

25% HIV & Poverty - Africa Botswana Lesotho 20% South Africa Namibia Zimbabwe Mozambique Zambia HIV Prevalence 15% 10% Malawi Central African Republic 5% 0% Côte d'ivoire Cameroon Tanzania Kenya Mauritania Ethiopia Senegal Sierra Leone 0 10 20 30 40 50 60 70 80 Percentage below $1 per day Ghana Burkina Faso Uganda Rwanda Burundi Gambia Niger Madagascar Nigeria Mali

35% HIV & Income Inequality - Africa Swaziland 30% 25% Botswana Lesotho R 2 = 0.4881 p=0.005% HIV Prevalence 20% 15% Mozambique Malawi Zambia Zimbabwe South Africa Namibia 10% Central African Republic 5% 0% Tanzania Uganda Côte d'ivoire Kenya Cameroon Rwanda Burundi Nigeria Ethiopia Ghana Mali Senegal Niger 0.25 0.35 0.45 0.55 0.65 0.75 GINI Coefficient

HIV prevalence & Life expectancy Switzerland Norway Iceland 75 Chile Spain Japan Costa Rica New Zealand Uruguay Czech Israel Jordan Poland 70 Sri Lanka Republic Greece at birth 2000 Mexico Ukraine Malta Luxembourg Egypt Slovenia Morocco Malaysia Cuba Panama Portugal Cyprus United States of America China Suriname Jamaica Argentina Barbados Bulgaria Croatia Estonia 60 Armenia Georgia Bahrain Ecuador Belize Hungary South Korea Fiji Trinidad and Tobago Nicaragua Thailand Indonesia Mauritius Peru Sweden Honduras El Salvador Russia Mongolia Brazil Lithuania Australia Uzbekistan Guatemala Dominican Romania Bangladesh Latvia Ireland Guyana Republic Bhutan India Turkey Belgium Azerbaijan Philippines Belarus Canada 50 Tajikistan Pakistan Bolivia Maldives Colombia Denmark Turkmenistan Yemen Finland Nepal Algeria Papua New Netherlands Africa Ghana Guinea Italy Cambodia Madagascar France Haiti Sudan Equatorial Guinea Germany Senegal United Kingdom Americas Guinea-Bissau Togo South Africa Singapore Nigeria Benin Austria Kenya Cameroon 40 Namibia Arab Chad countries Ethiopia Uganda Côte d'ivoire Eritrea Mozambique Swaziland Asia Mali Burkina Faso LE at birth (healthy years), total Log 30 Burundi Malawi Rwanda Zambia Central African Republic Lesotho Zimbabwe Botswana Europe Angola 25 Sierra Leone size = HIV prevalence (age 15 49) 308 600 800 1 000 2 000 3 000 5 000 7 000 10 000 20 000 53 500 GDP per capita in 1995 international dollars Log

There is no one African epidemic: know your epidemic and act on it Upstream effects: structural drivers in Africa: poverty versus income equality: which is more powerful? Downstream impact: long wave impacts on poverty, GDP, human capital, social capital Responding to the interaction between HIV and poverty

Epidemic Curves, HIV, AIDS & Impact Numbers HIV prevalence A A 1 A 2 AIDS - cumulative SOCIAL AND ECONOMIC IMPACT B B 1 T 1 T 2 Time

Impact of AIDS on life expectancy in five African countries 1970 2010 Life expectancy at birth (years) 70 65 60 55 50 45 40 35 30 25 20 1970 1975 1980 1985 1990 1995 2000 2005 1975 1980 1985 1990 1995 2000 2005 2010 Botswana South Africa Swaziland Zambia Zimbabwe Source: United Nations Population Division (2004). World Population Prospects: The 2004 Revision, database. 4.1

Percentage of distribution of deaths by age in southern Africa, 1985 1990 1990 and 2000 2005 2005 Percentage of total deaths 40 35 30 25 20 15 10 5 0 0 4 5 19 20 29 30 39 40 49 50 59 60+ Age-groups : 1985-1990 2000-2005 Source: Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat (2005). World Population Prospects: The 2004 Revision. Highlights. New York: United Nations. 4.2

Lifetime risk of AIDS death for 15-year year-old boys, assuming unchanged or halved risk of becoming infected with HIV, selected countries 100% 90% Botswana Risk of dying of AIDS 80% 70% 60% 50% 40% 30% 20% 10% Côte d Ivoire Cambodia Burkina Faso South Africa Zambia Kenya Cambodia Burkina Faso Zimbabwe Kenya Côte d Ivoire Zimbabwe South Africa Zambia Botswana risk halved over next 15 years current level of risk maintained 0% 0% 5% 10% 15% 20% 25% 30% 35% 40% Current adult HIV prevalence rate Source: Zaba B, 2000 (unpublished data)

Projected reduction in African agricultural labour force due to HIV and AIDS by 2020 Namibia Botswana Zimbabwe Mozambique South Africa Kenya Malawi Uganda UR Tanzania Central African Republic Côte d Ivoire Cameroon 2020 2000 0 5 10 15 20 25 30 Projected labor force loss (%) by year Sources: ILO (2004). HIV/AIDS and work: global estimates, impact and responses 4.8

Human capital Rising morbidity & mortality leading to decreased productivity in public and private sector investment declines at family, community, public sector and private sector levels Private sector: loss of skilled workforce, increased training needs, reduced management expertise Public sector: reduced tax revenues at a time of increased demand for health care and social support, reduced investment in child education, effects on workforce, potential for eroded governance capacity GDP effects: reduction of 0.5% to 1.5% in GDP growth rate over a 10 to 20 year period in high HIV prevalence countries

Between 1990 and 2003, sub-saharan Africa s population of children orphaned by AIDS increased from less than 1 million to more than 12 million 20 16 Number of Orphans due to AIDS (millions) 12 8 4 0 1990 1995 2000 2003 2010 Source: Children on the Brink 2004. A Joint Report of New Orphan Estimates and a Framework for Action. Fig. 6.

Intergenerational effects Orphans: 13% less likely to attend school than non-orphans (maternal orphans, double orphans, girls) Orphans overwhelming capacity of social networks and traditional patterns of intergenerational dependency, creating an uneducated, unsocialized and uncared for generation Lost transmission of knowledge and skills between generations (cf Bell and Deverajan): cumulative weakening from generation to generation of human and social capital

People in sub-saharan Africa on antiretroviral treatment as percentage of those in need, 2002 2005 2005 2005 2002 2003 2004 Source: WHO/ (2005). Progress on global access to HIV antiretroviral therapy: An update on 3 by 5. Warwick 7.2 Univ.

Women as a percentage of all adults receiving antiretroviral therapy in 30 countries: actual versus expected percentages, 2005 a Sub-Saharan Saharan Africa Botswana Burundi Central African Republic Côte d'ivoire Ethiopia Ghana Kenya Malawi Mozambique Namibia Nigeria Rwanda South Africa UR Tanzania Uganda Zambia Zimbabwe a The expected percentage of women receiving ARV therapy is based on the percentage of people living with HIV/AIDS who are women 0% 20% 40% 60% 80% Latin America and Caribbean Argentina Brazil El Salvador Guyana Haiti Honduras Panama Peru Venezuela Cambodia China India Viet Nam 0% 20% 40% 60% 80% Asia Expected percentage of women receiving ARV therapy 0% 20% 40% 60% 80% Source: WHO/ (2006). Progress on global access to HIV antiretroviral therapy. A report on 3 by 5 and beyond. 7.4

Comparison of 2003 and 2005 data on the expansion of antiretroviral ral therapy and coverage of HIV-infected mothers who received antiretroviral prophylaxis in three sub-saharan African countries Coverage of antiretroviral therapy Coverage of HIV-infected mothers who received antiretroviral prophylaxis 60 50 56.0 60 50 40 35.0 40 % 30 % 30 25.0 20 10 0 3.0 19.7 Kenya 0.0 Namibia 6.3 Uganda 20 10 0 1.0 9.3 Kenya 7.0 Namibia 4.6 12.0 Uganda Sources: Individual country reports (2005). 2003 2005 3.3

Impact of three scenarios on HIV infection in sub-saharan Africa, 2003 2020 2020 5.0 4.0 Number of new HIV infections (millions) 3.0 2.0 1.0 0.0 2003 2005 2010 2015 2020 Year Baseline Prevention-centered Treatment-centered Comprehensive response Source: Salomon JA et al. (2005). Integrating HIV prevention and treatment: from slogans to impact Warwick 6.1 Univ.

Impact of AIDS-related deaths in sub-saharan Africa, 2003 2020 2020 3.0 2.5 Number of AIDSrelated deaths (millions) 2.0 1.5 1.0 0.5 0.0 2003 2005 2010 2015 2020 Year Baseline Prevention-centered Treatment-centered Comprehensive response Source: Salomon JA et al. (2005). Integrating HIV prevention and treatment: from slogans to impact 6.2

There is no one African epidemic: know your epidemic and act on it Upstream effects: structural drivers in Africa: poverty versus income equality: which is more powerful? Downstream impact: long wave impacts on poverty, GDP, human capital, social capital Responding to the interaction between HIV and poverty

Targets and timelines UNGASS young people HIV-infected 25% reduction in most affected countries 2005; 25% globally 2010 UNGASS MTCT: % HIV + infants born to HIV-infected mothers 20% reduction by 2005; 50% reduction by 2010 3 by 5 Initiative: 3 million on ART by end 2005 Setting of next target? US President's Emergency Plan 2008 2 million on treatment, 7 million infections prevented, 10 million people, including orphans, provided with care Millennium Development Goals 2015 Halt and begin to reverse the spread of HIV/AIDS Global Fund rolling targets over 5 years (replenishment 2006, ) 1.6 million on treatment, 52 million reached by VCT; 1 million orphans

AIDS funding requirements for low- and middle-income income countries US$ billion 2006 2008 2006 2008 Prevention 8.4 10.0 11.4 29.8 Care and treatment 3.0 4.0 5.3 12.3 Support for orphans and vulnerable children 1.6 2.1 2.7 6.4 Programme costs 1.5 1.4 1.8 4.6 Human resources 0.4 0.6 0.9 1.9 TOTAL 14.9 18.1 22.1 55.1 Source: (2005). Resource needs for an expanded response to AIDS in low- and middle-income countries. 10.1

Sources of the estimated and projected funding for the AIDS response from 2005 to * 12 US$ billion 10 8 6 4 2 Private Sector Multilateral Bilateral Domestic 0 2005 2006 * Assuming there are no new commitments Source: (2005). Resource needs for an expanded response to AIDS in low- and middle-income countries. Warwick 10.10 Univ.

Impact of external grants on the macroeconomy at country level If small share in GDP, no problem If grants used to purchase imports (e.g. drugs), not much of a problem this is similar to receiving commodities If grants used to purchase nontradeables (goods or services that you can t import) then it creates demand for local goods and services; in large amounts, it pushes up their prices which disproportionately affects poor people It also pushes up demand for local currency, appreciating the exchange rate which can have a potentially adverse effect on exporters. Can you use grants to improve supply-side of economy reduce key bottlenecks? Adverse impact on revenue mobilization? Creates dependency? Advantages of debt relief

Progress towards achieving the Three Ones : Percentage of countries with one national coordinating body, one national HIV/AIDS strategy or framework and one national monitoring and evaluation plan 100 80 85 90 % 60 40 50 20 0 National body National frameworknational monitoring and evaluation plan 3.10

Stakeholder participation in development of national AIDS plans in 79 countries, 2004 UN agencies Civil society/ngos People living with HIV Donors Line ministries Media District and local authorities Faith-based organizations Private sector Women s groups 0% 20% 40% 60% 80% 100% full participation insufficient but increasing participation insufficient participation with no signs of improvement no participation Source: ( 2006) From advocacy to action: A progress report on at country-level,. Warwick 11.1 Univ.

Addressing AIDS in the poorest communities and countries AIDS money has most impact when strategies are based on the concept of know and act on your epidemic. Combine HIV programmes with poverty reduction initiatives. e.g. NGOs integrating HIV prevention into village/community banking programmes/microfinance (Malawi) for women, and combine AIDS education with the provision of microfinance to groups of women: need to shift from small-scale scale projects to large-scale programmes. Provision of HIV treatment can help prevent poverty, delay orphaning and indirectly contribute to HIV prevention as well. Development plans (whether they concern the development of productive sectors or the provision of social safety nets) must pass the AIDS test. e.g. World Bank-supported Chad/Cameroon Pipeline Project, supports HIV workplace interventions along the pipeline route both for workers and for affected communities Poverty reduction programmes and AIDS strategies must both reduce vulnerability particularly of women and young people: protecting human rights and tackling issues around social marginalization and stigma. Increased and sustained international support, driven by high-level political commitment and anchored in country ownership.

Acknowledgements Peter Piot Michel Sidibe Robert Greener Efren Fadriquela Mihika Acharya Constance Kponvi YOU, THE AUDIENCE THANK YOU!