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Tapestry of Complexity

Seroconversion (-)(+) (+)  +  -  +  +  +  +  -  +  +    +  -  +  +  -  +  +  -  +    +  -  +  +  +  -  +  +  -    +  +  -  +  +  +  +  +  + (-)(+)  (+). Tapestry of Complexity.

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Tapestry of Complexity

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  1. Seroconversion(-)(+) (+)+ - + + + + - + +  + - + + - + + - +  + - + + + - + + -  + + - + + + + + +(-)(+)(+)Seroconversion(-)(+) (+)+ - + + + + - + +  + - + + - + + - +  + - + + + - + + -  + + - + + + + + +(-)(+)(+)

  2. Tapestry of Complexity Are our data elements consistent when collecting data? Epidemiologic Are our surveillance systems reporting data consistently? Can they link together? Surveillance Are our intervention and care programs clearly distinguishable across characteristics? Prevention & Care Capacity- Building/ Tech. Asst. Do our training systems or data forms use consistent terminology? Are the intervention programs effective and under what criteria are we using? Does it really matter? Evaluation

  3. HIV and Its Complexities Prevention Treatment Care • Target Populations • Men who have sex with men (MSM) • High risk heterosexual (HRH) • Injection drug users (IDU) • Men who have sex with men/Injection Drug Users (MSM/IDU)

  4. Scientific Intervention Inconsistencies • Labels/TerminologyCharacteristics • Individual Level -- Duration/Dosage • Group Level -- Method of Delivery • Prevention Case Mgmt.-- Setting/Venue • Street Outreach -- Provider • Hlth. Comm/Pub. Info. -- Target Population • PCRS -- Cost (???) • Community Level -- Theory -- Outcomes CODING

  5. Documented available international resources for HIV/AIDS: 2002 United States of America 30% United Nations system organizations 27% Other donor countries* 13% United Kingdom 14% *Members of the Development Assistance Committee of the OECD Canada, France, Germany, Italy, Japan 9% Foundations 7% Source: UNAIDS, 2002

  6. Worldwide, AIDS kills more than 8,000 people every day; 1 person every 10 seconds.

  7. Adults and Children Estimated to be Living With HIV/AIDS, end 2003 Total: 34 - 46 million

  8. Percentage of workforce lost to AIDS by 2005 and 2020 in selected African countries 50 2005 2020 40 30 % 20 10 0 Botswana Côte d’Ivoire Togo Mozambique Ethiopia Cameroon Nigeria UR Tanzania CAR Zimbabwe Guinea-Bissau South Africa Sources: ILO (2000) POPILO population and labour force projection; UN Department of Economic and Social Affairs, Population Division (1998) World Population Prospects: the 1998 Revision

  9. Global Superstitions and Beliefs • Monkey’s transmitted the HIV virus • Man made—genetic manipulation • Having sex with a virgin can cure AIDS • Condoms don’t work • HIV is NOT the virus that causes AIDS

  10. The impact of HIV/AIDS on industries: an overview Loss Increased Increased Loss Declining of tacit absenteeism staff turnover of skills morale knowledge Insurance cover Increasing demands Retirement funds HIV/AIDS in for training and the country recruitment Health and safety Reduced Declining Declining markets, foreign intellectual labour pool, Medical assistance direct capital suppliers investment Funeral costs Declining Declining re - investment reliability Declining Increased costs productivity Declining profits Source: UNAIDS (2000) Adapted from The Business Response to HIV/AIDS: impact and lessons learned

  11. Major Causes of AIDS • Prostitution • Lack of sexual education • Unsafe sex due to either poor education or lack of money • Power imbalance between men and women • Polygamy

  12. HIV is More Than Just a Disease; It’s More Than Just an Epidemiological Exercise: It’s a Human Rights Issue, It’s a Women’s Issue. Why? Lack of control Poor reproductive and sexual health Neglect of health needs Clinical management All forms of coerced sex Harmful cultural practices Stigma and discrimination Access to education for prevention Sexual abuse Disclosure of status, partner notification, confidentiality

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