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Posterior Estimates of Dynamic Constants in HIV Transmission Modeling

In this paper, we construct a linear differential system in both continuous time and discrete time to model HIV transmission on the population level. The main question is the determination of parameters based on the posterior information obtained from statistical analysis of the HIV population. We c...

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Autores principales: Chen, Yingqing, Dale, Renee, He, Hongyu, Le, Quoc-Anh T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5698610/
https://www.ncbi.nlm.nih.gov/pubmed/29250132
http://dx.doi.org/10.1155/2017/1093045
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author Chen, Yingqing
Dale, Renee
He, Hongyu
Le, Quoc-Anh T.
author_facet Chen, Yingqing
Dale, Renee
He, Hongyu
Le, Quoc-Anh T.
author_sort Chen, Yingqing
collection PubMed
description In this paper, we construct a linear differential system in both continuous time and discrete time to model HIV transmission on the population level. The main question is the determination of parameters based on the posterior information obtained from statistical analysis of the HIV population. We call these parameters dynamic constants in the sense that these constants determine the behavior of the system in various models. There is a long history of using linear or nonlinear dynamic systems to study the HIV population dynamics or other infectious diseases. Nevertheless, the question of determining the dynamic constants in the system has not received much attention. In this paper, we take some initial steps to bridge such a gap. We study the dynamic constants that appear in the linear differential system model in both continuous and discrete time. Our computations are mostly carried out in Matlab.
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spelling pubmed-56986102017-12-17 Posterior Estimates of Dynamic Constants in HIV Transmission Modeling Chen, Yingqing Dale, Renee He, Hongyu Le, Quoc-Anh T. Comput Math Methods Med Research Article In this paper, we construct a linear differential system in both continuous time and discrete time to model HIV transmission on the population level. The main question is the determination of parameters based on the posterior information obtained from statistical analysis of the HIV population. We call these parameters dynamic constants in the sense that these constants determine the behavior of the system in various models. There is a long history of using linear or nonlinear dynamic systems to study the HIV population dynamics or other infectious diseases. Nevertheless, the question of determining the dynamic constants in the system has not received much attention. In this paper, we take some initial steps to bridge such a gap. We study the dynamic constants that appear in the linear differential system model in both continuous and discrete time. Our computations are mostly carried out in Matlab. Hindawi 2017 2017-11-07 /pmc/articles/PMC5698610/ /pubmed/29250132 http://dx.doi.org/10.1155/2017/1093045 Text en Copyright © 2017 Yingqing Chen et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Chen, Yingqing
Dale, Renee
He, Hongyu
Le, Quoc-Anh T.
Posterior Estimates of Dynamic Constants in HIV Transmission Modeling
title Posterior Estimates of Dynamic Constants in HIV Transmission Modeling
title_full Posterior Estimates of Dynamic Constants in HIV Transmission Modeling
title_fullStr Posterior Estimates of Dynamic Constants in HIV Transmission Modeling
title_full_unstemmed Posterior Estimates of Dynamic Constants in HIV Transmission Modeling
title_short Posterior Estimates of Dynamic Constants in HIV Transmission Modeling
title_sort posterior estimates of dynamic constants in hiv transmission modeling
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5698610/
https://www.ncbi.nlm.nih.gov/pubmed/29250132
http://dx.doi.org/10.1155/2017/1093045
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