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In-host modeling

Understanding the mechanisms governing host-pathogen kinetics is important and can guide human interventions. In-host mathematical models, together with biological data, have been used in this endeavor. In this review, we present basic models used to describe acute and chronic pathogenic infections....

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Detalles Bibliográficos
Autores principales: Ciupe, Stanca M., Heffernan, Jane M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: KeAi Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6001971/
https://www.ncbi.nlm.nih.gov/pubmed/29928736
http://dx.doi.org/10.1016/j.idm.2017.04.002
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author Ciupe, Stanca M.
Heffernan, Jane M.
author_facet Ciupe, Stanca M.
Heffernan, Jane M.
author_sort Ciupe, Stanca M.
collection PubMed
description Understanding the mechanisms governing host-pathogen kinetics is important and can guide human interventions. In-host mathematical models, together with biological data, have been used in this endeavor. In this review, we present basic models used to describe acute and chronic pathogenic infections. We highlight the power of model predictions, the role of drug therapy, and advantage of considering the dynamics of immune responses. We also present the limitations of these models due in part to the trade-off between the complexity of the model and their predictive power, and the challenges a modeler faces in determining the appropriate formulation for a given problem.
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spelling pubmed-60019712018-06-20 In-host modeling Ciupe, Stanca M. Heffernan, Jane M. Infect Dis Model Article Understanding the mechanisms governing host-pathogen kinetics is important and can guide human interventions. In-host mathematical models, together with biological data, have been used in this endeavor. In this review, we present basic models used to describe acute and chronic pathogenic infections. We highlight the power of model predictions, the role of drug therapy, and advantage of considering the dynamics of immune responses. We also present the limitations of these models due in part to the trade-off between the complexity of the model and their predictive power, and the challenges a modeler faces in determining the appropriate formulation for a given problem. KeAi Publishing 2017-04-29 /pmc/articles/PMC6001971/ /pubmed/29928736 http://dx.doi.org/10.1016/j.idm.2017.04.002 Text en © 2017 KeAi Communications Co., Ltd. Production and hosting by Elsevier B.V. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Ciupe, Stanca M.
Heffernan, Jane M.
In-host modeling
title In-host modeling
title_full In-host modeling
title_fullStr In-host modeling
title_full_unstemmed In-host modeling
title_short In-host modeling
title_sort in-host modeling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6001971/
https://www.ncbi.nlm.nih.gov/pubmed/29928736
http://dx.doi.org/10.1016/j.idm.2017.04.002
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