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Genotype-Structured Modeling of Variant Emergence and Its Impact on Virus Infection

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  • Anass Bouchnita

    (Department of Mathematical Sciences, The University of Texas at El Paso, El Paso, TX 79968, USA)

Abstract

Variant emergence continues to pose a threat to global public health, despite the large-scale campaigns of immunization worldwide. In this paper, we present a genotype-structured model of viral infectious and evolutionary dynamics. We calibrate the model using the available estimates for SARS-CoV-2 infection parameters and use it to study the conditions leading to the emergence of immune escaping variants. In particular, we show that the emergence of highly replicating or immune escaping variants could extend the duration of the infection, while the emergence of variants that are both highly replicating and immune escaping could provoke a rebound of the infection. Then, we show that the high frequency of mutation increases the chances of variant emergence, which promotes virus persistence. Further, simulations suggest that weak neutralization by antibodies could exert a selective pressure that favors the development of aggressive variants. These results can help public health officials identify and isolate the patients from where new variants emerge, which would make genomic surveillance efforts more efficient.

Suggested Citation

  • Anass Bouchnita, 2025. "Genotype-Structured Modeling of Variant Emergence and Its Impact on Virus Infection," Mathematics, MDPI, vol. 13(1), pages 1-13, January.
  • Handle: RePEc:gam:jmathe:v:13:y:2025:i:1:p:167-:d:1560692
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