Literature DB >> 26362230

Comparison of mathematical frameworks for modeling erythropoiesis in the context of malaria infection.

Luis L Fonseca1, Eberhard O Voit2.   

Abstract

Malaria is an infectious disease present all around the globe and responsible for half a million deaths per year. A within-host model of this infection requires a framework capable of properly approximating not only the blood stage of the infection but also the erythropoietic process that is in charge of overcoming the malaria induced anemia. Within this context, we compare ordinary differential equations (ODEs) with and without age classes, delayed differential equations (DDEs), and discrete recursive equations (DREs) with age classes. Results show that ODEs without age classes are fair approximations that do not provide a crisp temporal representation of the processes involved, and inclusion of age classes only mitigates the problem to some degree. DDEs perform well with respect to generating the essentially fixed delay between cell production and cell removal due to age, but the inclusion of any other processes, such as sudden blood loss, becomes cumbersome. The framework that was found to perform best in representing the dynamics of red blood cells during malaria infection is a DRE with age classes. In this model structure, the amount of time a cell remains alive is easily controlled, and the addition of age dependent or independent processes is straightforward. All events that populations of cells face during their lifespan, like growth or adaptation in differentiation or maturation rate, are properly represented in this framework.
Copyright © 2015. Published by Elsevier Inc.

Entities:  

Keywords:  DDE; Discrete recursive equation; Erythropoiesis; Malaria; ODE; Within-host model

Mesh:

Year:  2015        PMID: 26362230      PMCID: PMC4679698          DOI: 10.1016/j.mbs.2015.08.020

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  24 in total

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  12 in total

Review 1.  From within host dynamics to the epidemiology of infectious disease: Scientific overview and challenges.

Authors:  Juan B Gutierrez; Mary R Galinski; Stephen Cantrell; Eberhard O Voit
Journal:  Math Biosci       Date:  2015-10-16       Impact factor: 2.144

2.  Metabolic modeling helps interpret transcriptomic changes during malaria.

Authors:  Yan Tang; Anuj Gupta; Swetha Garimalla; Mary R Galinski; Mark P Styczynski; Luis L Fonseca; Eberhard O Voit
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6.  Examining the Reticulocyte Preference of Two Plasmodium berghei Strains during Blood-Stage Malaria Infection.

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8.  Replicative cellular age distributions in compartmentalized tissues.

Authors:  Marvin A Böttcher; David Dingli; Benjamin Werner; Arne Traulsen
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9.  Analysis of erythrocyte dynamics in Rhesus macaque monkeys during infection with Plasmodium cynomolgi.

Authors:  Luis L Fonseca; Chester J Joyner; Celia L Saney; Alberto Moreno; John W Barnwell; Mary R Galinski; Eberhard O Voit
Journal:  Malar J       Date:  2018-11-06       Impact factor: 2.979

10.  Quantifying the removal of red blood cells in Macaca mulatta during a Plasmodium coatneyi infection.

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Journal:  Malar J       Date:  2016-08-12       Impact factor: 2.979

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