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Updated: Jun 30, 2026

Using Zebrafish Models of Human Influenza A Virus Infections to Screen Antiviral Drugs and Characterize Host Immune Cell Responses
Published on: January 20, 2017
Improving the realism of deterministic multi-strain models: implications for modelling influenza A
1Department of Infectious Disease Epidemiology, MRC Centre for Outbreak Analysis and Modelling, Imperial College Faculty of Medicine, Norfolk Place, London W2 1PG, UK. p.minayev@imperial.ac.uk
This study models pathogen evolution, showing that cross-immunity intensity impacts disease dynamics. Deterministic models capture some aspects but require stochasticity for a complete understanding of influenza evolution.
Area of Science:
- Epidemiology
- Evolutionary Biology
- Mathematical Modeling
Background:
- Understanding pathogen evolution, especially for antigenically variable viruses like influenza, is complex.
- Existing simulation models often lack analytical insight or biological realism.
- Simpler models have struggled to accurately describe observed evolutionary patterns.
Purpose of the Study:
- To develop more biologically realistic deterministic models for multi-strain pathogen transmission dynamics.
- To investigate how the intensity of cross-immunity, based on genetic distance between strains, influences pathogen evolution.
- To explore the role of transient strain-transcending immunity in regulating infection prevalence and pathogen diversity.
Main Methods:
- Development of deterministic mathematical models for pathogen transmission.
- Incorporation of strain-specific cross-immunity dependent on genetic dissimilarity.
- Inclusion of transient strain-transcending immunity as a density-dependent factor.
Main Results:
- Model dynamics are governed by cross-immune response parameters, leading to varied outcomes like equilibria, self-organized structures, periodic, and chaotic regimes.
- Transient immunity effectively reduces infection prevalence and pathogen diversity.
- Deterministic models can partially explain influenza evolution but are insufficient alone.
Conclusions:
- Deterministic models offer valuable insights into pathogen evolution but have limitations.
- Accurate modeling of influenza dynamics necessitates incorporating stochasticity in strain generation and extinction.
- Future research should integrate both deterministic and stochastic elements for comprehensive understanding.
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