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    Within-host infectious disease models accommodating cellular coinfection, with an application to influenza

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    Author
    Koelle, Katia
    Farrell, Alex P
    Brooke, Christopher B
    Ke, Ruian
    Affiliation
    Univ Arizona, Dept Math
    Issue Date
    2019-07-08
    Keywords
    cellular coinfection
    influenza virus
    macroparasite model
    viral complementation
    within-host dynamics
    
    Metadata
    Show full item record
    Publisher
    OXFORD UNIV PRESS
    Citation
    Katia Koelle, Alex P Farrell, Christopher B Brooke, Ruian Ke, Within-host infectious disease models accommodating cellular coinfection, with an application to influenza, Virus Evolution, Volume 5, Issue 2, July 2019, vez018, https://doi.org/10.1093/ve/vez018
    Journal
    VIRUS EVOLUTION
    Rights
    Copyright © The Author(s) 2019. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    Within-host models are useful tools for understanding the processes regulating viral load dynamics. While existing models have considered a wide range of within-host processes, at their core these models have shown remarkable structural similarity. Specifically, the structure of these models generally consider target cells to be either uninfected or infected, with the possibility of accommodating further resolution (e.g. cells that are in an eclipse phase). Recent findings, however, indicate that cellular coinfection is the norm rather than the exception for many viral infectious diseases, and that cells with high multiplicity of infection are present over at least some duration of an infection. The reality of these cellular coinfection dynamics is not accommodated in current within-host models although it may be critical for understanding within-host dynamics. This is particularly the case if multiplicity of infection impacts infected cell phenotypes such as their death rate and their viral production rates. Here, we present a new class of within-host disease models that allow for cellular coinfection in a scalable manner by retaining the low-dimensionality that is a desirable feature of many current within-host models. The models we propose adopt the general structure of epidemiological 'macroparasite' models that allow hosts to be variably infected by parasites such as nematodes and host phenotypes to flexibly depend on parasite burden. Specifically, our within-host models consider target cells as 'hosts' and viral particles as 'macroparasites', and allow viral output and infected cell lifespans, among other phenotypes, to depend on a cell's multiplicity of infection. We show with an application to influenza that these models can be statistically fit to viral load and other within-host data, and demonstrate using model selection approaches that they have the ability to outperform traditional within-host viral dynamic models. Important in vivo quantities such as the mean multiplicity of cellular infection and time-evolving reassortant frequencies can also be quantified in a straightforward manner once these macroparasite models have been parameterized. The within-host model structure we develop here provides a mathematical way forward to address questions related to the roles of cellular coinfection, collective viral interactions, and viral complementation in within-host viral dynamics and evolution.
    Note
    Open access journal
    ISSN
    2057-1577
    PubMed ID
    31304043
    DOI
    10.1093/ve/vez018
    Version
    Final published version
    Sponsors
    DARPA INTERCEPT [W911NF-17-2-0034]; MIDAS CIDID Center of Excellence [U54-GM111274]
    ae974a485f413a2113503eed53cd6c53
    10.1093/ve/vez018
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    UA Faculty Publications

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