Issue |
Math. Model. Nat. Phenom.
Volume 20, 2025
Special Issue to honour Vitaly's work
|
|
---|---|---|
Article Number | 14 | |
Number of page(s) | 16 | |
DOI | https://doi.org/10.1051/mmnp/2025006 | |
Published online | 14 May 2025 |
The interplay between evolutionary and immunological dynamics regulates virus variant emergence and competition
1
Department of Mathematical Science, The University of Texas at El Paso,
El Paso, TX
79968, USA
2
Department of Integrative Biology, The Unviersity of Texas at Austin,
Austin, TX
78712, USA
3
School of Public Health, The University of Texas Health Science Center,
Houston, Texas,
77030, USA
4
Department of Epidemiology & Biostatistics, University of Georgia,
Athens, GA
30602, USA
5
Institute of Bioinformatics, University of Georgia,
Athens, GA
30602, USA
* Corresponding author: abouchnita@utep.edu
Received:
17
April
2024
Accepted:
3
February
2025
As viruses like SARS-CoV-2 and pandemic influenza become endemic, their spread is shaped by decreasing population immunity and the emergence of new variants that either spread more easily or bypass existing immunity. Traditional modeling of these dynamics has been challenging due to increased computational demands as the number of strains and immune profiles grow. We introduce a simplified epidemiological model that incorporates viral evolution, immunological and transmission dynamics, as well as variant-specific factors like disease severity. This model, based on the standard SIR framework and using a COVID-19 specific parameters, explores the interaction between immunological and evolutionary mechanisms. It suggests that in the absence of broad cross-immunity, different variants can co-exist together. The model predicts that viruses with higher transmissibility, mutation rates are more likely to evolve, while variants with reduced immune escape have a higher emergence potential. In scenarios where an emerging variant’s transmissibility doubles, the model forecasts a sevenfold increase in cases over 2,000 days. While parameterized using COVID-19 data, our model can be adapted for other viruses with evolving strains, such as influenza or Dengue. Hence, it promises to enhance our capacity to predict variant developments and guide public health strategies.
Mathematics Subject Classification: 92-10 / 92B05 / 45K05
Key words: Immuno-epidemiological modeling / genotype-structured models / epidemiological modeling / reactiondiffusion systems / genetic mutations
© The authors. Published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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