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Patterns of infection: using age prevalence data to understand epidemic of HIV in South Africa

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dc.contributor.author Williams, BG en_US
dc.contributor.author Gouws, E en_US
dc.contributor.author Colvin, M en_US
dc.contributor.author Sitas, F en_US
dc.contributor.author Ramjee, G en_US
dc.contributor.author Karim, SSA en_US
dc.date.accessioned 2007-03-14T07:57:30Z en_US
dc.date.accessioned 2007-06-07T10:09:11Z
dc.date.available 2007-03-14T07:57:30Z en_US
dc.date.available 2007-06-07T10:09:11Z
dc.date.issued 2000-06 en_US
dc.identifier.citation Williams, BG, et al. 2000. Patterns of infection: using age prevalence data to understand epidemic of HIV in South Africa. South African Journal of Science, vol. 96(6), pp 305-312 en_US
dc.identifier.issn 0038-2353 en_US
dc.identifier.uri http://hdl.handle.net/10204/1916 en_US
dc.identifier.uri http://hdl.handle.net/10204/1916
dc.description.abstract South Africa is experiencing an explosive epidemic of HIV/AIDS, with about one in four women attending ante-natal clinics nation-wide being HIV-positive. In order to understand the natural history of the epidemic, to design and target intervention to manage it and to evaluate the impact of intervention implemented. It is essential to gather information on the patterns of infection. In particular it is important to know how these vary with gender, age, migrancy status and between urban and rural settings. Ideally, one should measure age specific incidence but this is difficult to do. Many datasets are available, however, on age specific prevalence of infection and these are used to investigate the risk of infection with age among a number of different populations. The populations under consideration include women attending ante-natal clinics, urban and rural populations, migrant workers and commercial sex workers. Data are also presented from one work-based survey and from a study of cancer patients at a major hospital in Soweto. a) Women attending ante-natal clinics; b) Women in the general population; c) Men in the general population; and d) migrant workers, it is interesting that the authors were unable to show differences between urban and rural populations. Furthermore, the patterns of infection appear to be fairly constant over time, although as epidemic saturates and reaches a steady state this must change. These data highlight, in particular, the extremely high risk of infection among 15-25 years old women and among migrant workers of all ages. They should serve not only to highlight the urgency of the situation and the need to deal with the spread of infection effectively, but should also provide a basis for detailed epidemiological modelling, which can be used to predict the future course of the epidemic, plan an effective response and evaluate the impact of interventions. en_US
dc.format.extent 2229138 bytes en_US
dc.format.mimetype application/pdf en_US
dc.language.iso en en_US
dc.publisher Bureau Scientific Publications en_US
dc.rights Copyright: 2000 Bureau Scientific Publications en_US
dc.subject Infection patterns en_US
dc.subject HIV/AIDS en_US
dc.subject South Africa en_US
dc.title Patterns of infection: using age prevalence data to understand epidemic of HIV in South Africa en_US
dc.type Article en_US
dc.identifier.apacitation Williams, B., Gouws, E., Colvin, M., Sitas, F., Ramjee, G., & Karim, S. (2000). Patterns of infection: using age prevalence data to understand epidemic of HIV in South Africa. http://hdl.handle.net/10204/1916 en_ZA
dc.identifier.chicagocitation Williams, BG, E Gouws, M Colvin, F Sitas, G Ramjee, and SSA Karim "Patterns of infection: using age prevalence data to understand epidemic of HIV in South Africa." (2000) http://hdl.handle.net/10204/1916 en_ZA
dc.identifier.vancouvercitation Williams B, Gouws E, Colvin M, Sitas F, Ramjee G, Karim S. Patterns of infection: using age prevalence data to understand epidemic of HIV in South Africa. 2000; http://hdl.handle.net/10204/1916. en_ZA
dc.identifier.ris TY - Article AU - Williams, BG AU - Gouws, E AU - Colvin, M AU - Sitas, F AU - Ramjee, G AU - Karim, SSA AB - South Africa is experiencing an explosive epidemic of HIV/AIDS, with about one in four women attending ante-natal clinics nation-wide being HIV-positive. In order to understand the natural history of the epidemic, to design and target intervention to manage it and to evaluate the impact of intervention implemented. It is essential to gather information on the patterns of infection. In particular it is important to know how these vary with gender, age, migrancy status and between urban and rural settings. Ideally, one should measure age specific incidence but this is difficult to do. Many datasets are available, however, on age specific prevalence of infection and these are used to investigate the risk of infection with age among a number of different populations. The populations under consideration include women attending ante-natal clinics, urban and rural populations, migrant workers and commercial sex workers. Data are also presented from one work-based survey and from a study of cancer patients at a major hospital in Soweto. a) Women attending ante-natal clinics; b) Women in the general population; c) Men in the general population; and d) migrant workers, it is interesting that the authors were unable to show differences between urban and rural populations. Furthermore, the patterns of infection appear to be fairly constant over time, although as epidemic saturates and reaches a steady state this must change. These data highlight, in particular, the extremely high risk of infection among 15-25 years old women and among migrant workers of all ages. They should serve not only to highlight the urgency of the situation and the need to deal with the spread of infection effectively, but should also provide a basis for detailed epidemiological modelling, which can be used to predict the future course of the epidemic, plan an effective response and evaluate the impact of interventions. DA - 2000-06 DB - ResearchSpace DP - CSIR KW - Infection patterns KW - HIV/AIDS KW - South Africa LK - https://researchspace.csir.co.za PY - 2000 SM - 0038-2353 T1 - Patterns of infection: using age prevalence data to understand epidemic of HIV in South Africa TI - Patterns of infection: using age prevalence data to understand epidemic of HIV in South Africa UR - http://hdl.handle.net/10204/1916 ER - en_ZA


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