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

View ORCID ProfileKatia Koelle, Alex Farrell, Christopher Brooke, Ruian Ke
doi: https://doi.org/10.1101/359067
Katia Koelle
1Department of Biology, Emory University, Atlanta, GA 30322
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  • For correspondence: katia.koelle@emory.edu
Alex Farrell
2Department of Mathematics, North Carolina State University, Raleigh, NC 27695
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Christopher Brooke
3Department of Microbiology, University of Illinois at Urbana-Champaign, IL 61801
4Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, IL 61801
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Ruian Ke
2Department of Mathematics, North Carolina State University, Raleigh, NC 27695
5Comparative Medicine Institute, North Carolina State University, Raleigh, NC 27695
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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 (for example, cells that are refractory to infection and 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, that they can reproduce notable features of within-host viral dynamics, and that important in vivo quantities such as the mean multiplicity of cellular infection can be easily quantified with these models once parameterized. The within-host model structure we develop here provides an alternative approach for modeling within-host viral load dynamics and allows for a new class of questions to be addressed that consider the effects of cellular coinfection, collective viral interactions, and viral complementation in within-host viral dynamics and evolution.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted June 29, 2018.
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Within-host infectious disease models accommodating cellular coinfection, with an application to influenza
Katia Koelle, Alex Farrell, Christopher Brooke, Ruian Ke
bioRxiv 359067; doi: https://doi.org/10.1101/359067
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Within-host infectious disease models accommodating cellular coinfection, with an application to influenza
Katia Koelle, Alex Farrell, Christopher Brooke, Ruian Ke
bioRxiv 359067; doi: https://doi.org/10.1101/359067

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