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Mathematical modeling of the effect of multiple vaccines on viral escape

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  • Mohan, Tarun
  • Dobrovolny, Hana M.

Abstract

SARS-CoV-2 has become an endemic virus that is partly kept in check by annual vaccination. A number of different vaccines are available to prevent severe illness from SARS-CoV-2 infection. These vaccines are based on different vaccine modalities and have the potential to elicit slightly different immune responses. Unfortunately, more recent strains of SARS-CoV-2 appear to have the ability to evade some of the immune protection provided by vaccines. While the genesis for the large number of vaccines was the need to rapidly develop a vaccine that was effective against SARS-CoV-2, researchers have speculated that having multiple vaccines with different mechanisms would make it harder for the virus to mutate enough to evade all the vaccines. In this manuscript, we use mathematical models to determine whether use of multiple vaccines decreases the likelihood of evolving a virus strain that can evade all the vaccines. We use a series of models, ranging from one to three vaccines, to measure the fraction of fully escaped virus infections during an epidemic. We find that vaccination rates need to be higher (higher vaccine pressure) in order for a virus to escape all vaccines as the number of vaccines increases. This suggests that the use of multiple vaccines has a population-wide protective effect since this makes it more difficult for the virus to fully escape all vaccines.

Suggested Citation

  • Mohan, Tarun & Dobrovolny, Hana M., 2026. "Mathematical modeling of the effect of multiple vaccines on viral escape," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 241(PA), pages 408-429.
  • Handle: RePEc:eee:matcom:v:241:y:2026:i:pa:p:408-429
    DOI: 10.1016/j.matcom.2025.09.010
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    References listed on IDEAS

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    1. Aguilar-Canto, Fernando Javier & de León, Ugo Avila-Ponce & Avila-Vales, Eric, 2022. "Sensitivity theorems of a model of multiple imperfect vaccines for COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    2. Eunha Shim, 2021. "Projecting the Impact of SARS-CoV-2 Variants and the Vaccination Program on the Fourth Wave of the COVID-19 Pandemic in South Korea," IJERPH, MDPI, vol. 18(14), pages 1-11, July.
    3. Sylvain Gandon & Margaret J. Mackinnon & Sean Nee & Andrew F. Read, 2001. "Imperfect vaccines and the evolution of pathogen virulence," Nature, Nature, vol. 414(6865), pages 751-756, December.
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    5. Tsiligianni, Christiana & Tsiligiannis, Aristeides & Tsiliyannis, Christos, 2023. "A stochastic inventory model of COVID-19 and robust, real-time identification of carriers at large and infection rate via asymptotic laws," European Journal of Operational Research, Elsevier, vol. 304(1), pages 42-56.
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