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A couple of words on HIV at SANBI

A couple of words on HIV at SANBI. Minna Lehväslaiho SANBI, University of the Western Cape Workshop on the Representation of Phenotypes Stanford 1-Dec-2006. 1 December 2006 World AIDS day. Some South African statistics.

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A couple of words on HIV at SANBI

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  1. A couple of words onHIV at SANBI Minna Lehväslaiho SANBI, University of the Western Cape Workshop on the Representation of Phenotypes Stanford 1-Dec-2006

  2. 1 December 2006World AIDS day

  3. Some South African statistics • 2005: 5.5 million out of 47 million population was living with HIV (12%) • HIV prevalence among pregnant women: 1990: 0.8% (The first national antenatal survey) 1993: 4.3% 1996: 12.2% 1997: 17.0% 1999: 22.4% 2001: 24.8% 2003: 27.9%. 2005: 30.2%

  4. Some South African statistics • Survey in 2004: South Africans spend more time at funerals than having their hair cut, shopping or having a braai. • Survey in 2004: more than twice as many people had been to a funeral in the past month than had been to a wedding.

  5. Why? • Vice president’s prevention: take a shower • Health minister’s cure: Garlic, lemons and African potatoes. • The most prevalent strain in Africa is the C strain which is more aggressive and more easily spreads via heterosexual contact than the B strain found in Europe and US. • C strain: Africa -> South America • C strain: Africa -> India -> China

  6. What’s being done • Organizations such the International Red Cross and Red Crescent focus on prevention, care, treatment, and fighting stigma and discrimination • Government • South African National Bioinformatics Institute: CAPRISA http://www.caprisa.org/and SAAVI http://www.saavi.org.za/

  7. MID • The Molecular Integration Database for HIV data • Purpose: to integrate HIV biomedical information created by several laboratories into one query enabled interface • The level of organization in MID is that it is a relational database with a BIoMart query interface and a glossary of terms. • Potential for developing and contributing to host/pathogen ontology • Heikki@sanbi.ac.za

  8. eVOC • Built as ontologies for human gene expression, to unify gene expression data • eVOC Pathology describes the pathological state of the tissue from which the sample was prepared • http://www.evocontology.org/

  9. PML • Polymorphism Markup Language Project, PML • OMG Standard for Sequence variation and genotyping. It’s created in collaboration with SNP and sequence variation databases. • PML tries to be able to interface to ontologies used in healthcare. • www.openpml.org (not active yet) or contact Heikki@sanbi.ac.za

  10. Describing HIV • Infection / diagnosis / progress / treatment • Patient information / tissue samples / pathogen information • Medication

  11. SANBI Contributors Allan Kamau Adele Kruger Alan Powell Ulf Schafer Anelda Boardman Minna Lehväslaiho Heikki Lehväslaiho Oliver Hofmann Win Hide

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