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The Rise and Fall of HIV in High-Prevalence Countries: A Challenge for Mathematical Modeling

Several countries with generalized, high-prevalence HIV epidemics, mostly in sub-Saharan Africa, have experienced rapid declines in transmission. These HIV epidemics, often with rapid onsets, have generally been attributed to a combination of factors related to high-risk sexual behavior. The subsequ...

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Autores principales: Nagelkerke, Nico J. D., Arora, Paul, Jha, Prabhat, Williams, Brian, McKinnon, Lyle, de Vlas, Sake J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3952813/
https://www.ncbi.nlm.nih.gov/pubmed/24626088
http://dx.doi.org/10.1371/journal.pcbi.1003459
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author Nagelkerke, Nico J. D.
Arora, Paul
Jha, Prabhat
Williams, Brian
McKinnon, Lyle
de Vlas, Sake J.
author_facet Nagelkerke, Nico J. D.
Arora, Paul
Jha, Prabhat
Williams, Brian
McKinnon, Lyle
de Vlas, Sake J.
author_sort Nagelkerke, Nico J. D.
collection PubMed
description Several countries with generalized, high-prevalence HIV epidemics, mostly in sub-Saharan Africa, have experienced rapid declines in transmission. These HIV epidemics, often with rapid onsets, have generally been attributed to a combination of factors related to high-risk sexual behavior. The subsequent declines in these countries began prior to widespread therapy or implementation of any other major biomedical prevention. This change has been construed as evidence of behavior change, often on the basis of mathematical models, but direct evidence for behavior changes that would explain these declines is limited. Here, we look at the structure of current models and argue that the common “fixed risk per sexual contact" assumption favors the conclusion of substantial behavior changes. We argue that this assumption ignores reported non-linearities between exposure and risk. Taking this into account, we propose that some of the decline in HIV transmission may be part of the natural dynamics of the epidemic, and that several factors that have traditionally been ignored by modelers for lack of precise quantitative estimates may well hold the key to understanding epidemiologic trends.
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spelling pubmed-39528132014-03-18 The Rise and Fall of HIV in High-Prevalence Countries: A Challenge for Mathematical Modeling Nagelkerke, Nico J. D. Arora, Paul Jha, Prabhat Williams, Brian McKinnon, Lyle de Vlas, Sake J. PLoS Comput Biol Review Several countries with generalized, high-prevalence HIV epidemics, mostly in sub-Saharan Africa, have experienced rapid declines in transmission. These HIV epidemics, often with rapid onsets, have generally been attributed to a combination of factors related to high-risk sexual behavior. The subsequent declines in these countries began prior to widespread therapy or implementation of any other major biomedical prevention. This change has been construed as evidence of behavior change, often on the basis of mathematical models, but direct evidence for behavior changes that would explain these declines is limited. Here, we look at the structure of current models and argue that the common “fixed risk per sexual contact" assumption favors the conclusion of substantial behavior changes. We argue that this assumption ignores reported non-linearities between exposure and risk. Taking this into account, we propose that some of the decline in HIV transmission may be part of the natural dynamics of the epidemic, and that several factors that have traditionally been ignored by modelers for lack of precise quantitative estimates may well hold the key to understanding epidemiologic trends. Public Library of Science 2014-03-13 /pmc/articles/PMC3952813/ /pubmed/24626088 http://dx.doi.org/10.1371/journal.pcbi.1003459 Text en © 2014 Nagelkerke et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Review
Nagelkerke, Nico J. D.
Arora, Paul
Jha, Prabhat
Williams, Brian
McKinnon, Lyle
de Vlas, Sake J.
The Rise and Fall of HIV in High-Prevalence Countries: A Challenge for Mathematical Modeling
title The Rise and Fall of HIV in High-Prevalence Countries: A Challenge for Mathematical Modeling
title_full The Rise and Fall of HIV in High-Prevalence Countries: A Challenge for Mathematical Modeling
title_fullStr The Rise and Fall of HIV in High-Prevalence Countries: A Challenge for Mathematical Modeling
title_full_unstemmed The Rise and Fall of HIV in High-Prevalence Countries: A Challenge for Mathematical Modeling
title_short The Rise and Fall of HIV in High-Prevalence Countries: A Challenge for Mathematical Modeling
title_sort rise and fall of hiv in high-prevalence countries: a challenge for mathematical modeling
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3952813/
https://www.ncbi.nlm.nih.gov/pubmed/24626088
http://dx.doi.org/10.1371/journal.pcbi.1003459
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