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Within-host influenza dynamics: a small-scale mathematical modeling approach.

Himanshu Manchanda1, Nora Seidel2, Andi Krumbholz3

  • 1Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute, Jena, Germany; Jena University Hospital, Department of Virology and Antiviral Therapy, Jena, Germany.

Bio Systems
|March 12, 2014
PubMed
Summary

A new mathematical model explains influenza kinetics in mice, revealing inflammation as the cause of biphasic disease courses. This aids in developing new antiviral treatments against influenza A virus strains.

Keywords:
Immune responseInfectionInflammationInfluenza virusModelingVirus replication

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Area of Science:

  • Virology and Mathematical Biology
  • Infectious Disease Modeling
  • Immunology

Background:

  • Emerging influenza viruses, such as pandemic H1N1 influenza A virus (A(H1N1)pdm09), present challenges for vaccine coverage and antiviral treatments.
  • There is a need for robust murine models to evaluate novel antiviral compounds in vivo.
  • Understanding influenza kinetics is crucial for developing effective therapeutic strategies.

Purpose of the Study:

  • To develop a small-scale mathematical model for analyzing influenza kinetics in mice.
  • To explain variations in influenza progression caused by different virus strains.
  • To quantitatively study influenza dynamics using easily obtainable experimental data.

Main Methods:

  • Development of a three-dimensional ordinary differential equation model incorporating viral pathogenicity (P), immune defense (D), and inflammation (I).
  • Utilizing clinical scores (S) in mice to calculate pathogenicity and inflammation parameters.
  • Fitting the mathematical model to experimental data from influenza A virus infections (A(H1N1)pdm09 and H1N2) exhibiting mono- and biphasic courses.

Main Results:

  • The model successfully explains differences in influenza kinetics induced by various virus strains in mice.
  • Analysis of mono- and biphasic influenza courses caused by A(H1N1)pdm09 and H1N2 viruses.
  • Modeling results indicate that inflammation is the primary driver of the second peak in biphasic influenza infections.

Conclusions:

  • The developed mathematical model provides insights into the mechanisms underlying mild and severe influenza, including biphasic disease patterns.
  • Key parameters characterizing influenza kinetics include maximum primary pathogenicity, viral infection rate, and immune system activation rate.
  • This modeling approach can aid in evaluating antiviral compound efficacy in vivo and understanding virus-specific influenza dynamics.