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Modelling the demographic impact of HIV/AIDS in South Africa and the likely impact of interventions

Author

Listed:
  • Leigh F. Johnson

    (University of Cape Town (UCT))

  • Rob Dorrington

    (University of Cape Town (UCT))

Abstract

This paper describes an approach to incorporating the impact of HIV/AIDS and the effects of HIV/AIDS prevention and treatment programmes into a cohort component projection model of the South African population. The modelled HIV-positive population is divided into clinical and treatment stages, and it is demonstrated that the age profile and morbidity profile of the HIV-positive population is changing significantly over time. HIV/AIDS is projected to have a substantial demographic impact in South Africa. Prevention programmes - social marketing, voluntary counselling and testing, prevention of mother-to-child transmission and improved treatment for sexually transmitted diseases - are unlikely to reduce AIDS mortality significantly in the short term. However, more immediate reductions in mortality can be achieved when antiretroviral treatment is introduced.

Suggested Citation

  • Leigh F. Johnson & Rob Dorrington, 2006. "Modelling the demographic impact of HIV/AIDS in South Africa and the likely impact of interventions," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 14(22), pages 541-574.
    • Handle: RePEc:dem:demres:v:14:y:2006:i:22
    DOI: 10.4054/DemRes.2006.14.22
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    File URL: https://www.demographic-research.org/volumes/vol14/22/14-22.pdf
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    References listed on IDEAS

    as
    1. Eline Korenromp & Carina van Vliet & Roel Bakker & Sake de Vlas & J. Dik & F. Habbema, 2000. "HIV spread and partnership reduction for different patterns of sexual behaviour - a study with the microsimulation model STDSIM," Mathematical Population Studies, Taylor & Francis Journals, vol. 8(2), pages 135-173.
    2. Catharina P. B. Van der Ploeg & Carina Van Vliet & Sake J. De Vlas & Jeckoniah O. Ndinya-Achola & Lieve Fransen & Gerrit J. Van Oortmarssen & J. Dik F. Habbema, 1998. "STDSIM: A Microsimulation Model for Decision Support in STD Control," Interfaces, INFORMS, vol. 28(3), pages 84-100, June.
    3. Patrick Heuveline, 2003. "HIV and population dynamics: A general model and maximum-likelihood standards for East Africa," Demography, Springer;Population Association of America (PAA), vol. 40(2), pages 217-245, May.
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    Citations

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    Cited by:

    1. Bell, Clive & Gersbach, Hans, 2009. "The macroeconomics of targeting: the case of an enduring epidemic," Journal of Health Economics, Elsevier, vol. 28(1), pages 54-72, January.
    2. Leigh Johnson & Rob Dorrington & Debbie Bradshaw & Victoria Pillay-Van Wyk & Thomas Rehle, 2009. "Sexual behaviour patterns in South Africa and their association with the spread of HIV: insights from a mathematical model," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 21(11), pages 289-340.
    3. Carel Pretorius & John Stover & Lori Bollinger & Nicolas Bacaër & Brian Williams, 2010. "Evaluating the Cost-Effectiveness of Pre-Exposure Prophylaxis (PrEP) and Its Impact on HIV-1 Transmission in South Africa," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-10, November.
    4. Louise Roos, 2013. "Modelling the impact of HIV/AIDS: A literature review," Centre of Policy Studies/IMPACT Centre Working Papers g-233, Victoria University, Centre of Policy Studies/IMPACT Centre.

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    More about this item

    Keywords

    South Africa; simulation; demographic impact; HIV/AIDS prevention; antiretroviral therapy;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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