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A deterministic model for influenza infection with multiple strains and antigenic drift
Jorge A Alfaro-Murillo1, Sherry Towers, Zhilan Feng
1Department of Mathematics, Purdue University, West Lafayette, IN, USA. alfaro@math.purdue.edu
Journal of Biological Dynamics
|May 25, 2013
Summary
This study presents a novel influenza model accounting for new strains and partial immunity. The model successfully replicates real-world influenza outbreak patterns in different climates.
Area of Science:
- Epidemiology
- Mathematical Biology
- Virology
Background:
- Influenza virus dynamics are complex, influenced by factors like antigenic drift and population immunity.
- Understanding seasonal and geographical variations in influenza outbreaks is crucial for public health.
Purpose of the Study:
- To develop a deterministic mathematical model simulating influenza spread considering multiple strains and partial immunity.
- To investigate the impact of antigenic drift and seasonal forcing on influenza epidemic patterns.
Main Methods:
- A Susceptible-Infected-Recovered (SIR) compartmental model was adapted to include multiple influenza strains.
- The model incorporated mechanisms for the emergence of new strains via antigenic drift and waning/partial immunity.
- Optional seasonal forcing was applied to the transmission rate to simulate geographical differences.
Main Results:
- The model accurately reproduced key epidemiological patterns, including annual outbreaks in temperate regions.
- It captured the reduced magnitude and increased frequency of tropical outbreaks.
- The model also demonstrated the 'herald wave' phenomenon, a precursor to major epidemics.
Conclusions:
- The developed model provides a robust framework for understanding complex influenza dynamics.
- The novel approach to modeling antigenic drift offers insights into viral evolution and spread.
- Further model modifications can enhance our comprehension of influenza epidemiology.
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