Mathematical Modeling and Analysis of Influenza In-Host Infection Dynamics

Blessing O. Emerenini
School of Mathematical Sciences, Rochester Institute of Technology, Rochester NY, USA

Reed Williams
State University of New York at New Paltz, NY, USA

Ricardo N. G. Reyes Grimaldo
Department of Integrative Biology, Oregon State University, OR, USA

Krista Wurscher
University of Oregon, Eugene, OR, USA

Ekeoma R. Ijioma
Department of Mathematics and Statistics, University of Limerick, Limerick, Ireland

Abstract

Influenza is a viral infectious disease of high importance widely studied around the world. In this study we model within-host transmission of influenza in a continuous deterministic setting, a discrete stochastic framework and a spatial-temporal model. Previous models omit cellular restoration through cellular death, which is a key component for the possibility of chronic infections. We thus investigate the effect of cellular restoration on the spread of influenza within the host, through stability analysis of the deterministic model, the probability of state transitions in the stochastic model and the effect of mobility rates on disease spread in the spatial-temporal model. Using the Partial Rank Correlation Coefficient and the Latin Hypercube Sampling, we performed sensitivity analysis to determine which of the parameters are most influential to the model output.

Keywords: Mathematical modeling ,Influenza ,In-host infection dynamics ,Stochastic

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