Mutant emergence timing and population immunisation status impact epidemiological dynamics

•Immune waning leads to varying levels of immunity in the population.•We developed a non-Markovian two-strain model to assess mutant invasion.•The same mutant may or may not invade depending solely on its timing of introduction.•Markovian models assuming endemic equilibrium would miss these dynamics...

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Published inJournal of theoretical biology Vol. 608; p. 112140
Main Authors Reyné, Bastien, Djidjou-Demasse, Ramsès, Sofonea, Mircea T., Alizon, Samuel
Format Journal Article
LanguageEnglish
Published England Elsevier Ltd 07.07.2025
Elsevier
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ISSN0022-5193
1095-8541
1095-8541
DOI10.1016/j.jtbi.2025.112140

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Summary:•Immune waning leads to varying levels of immunity in the population.•We developed a non-Markovian two-strain model to assess mutant invasion.•The same mutant may or may not invade depending solely on its timing of introduction.•Markovian models assuming endemic equilibrium would miss these dynamics. A key question in evolutionary epidemiology is to determine differences in the conditions that may allow some mutant strains to spread in a population where a resident strain is already circulating. Evolutionary invasion analyses assume that the immunity is long-lasting for previously infected individuals making it difficult to study traits such as immune escape. We relax this last assumption and allow the environment faced by the mutant to fluctuate outside of any epidemiological equilibrium. We introduce an original two-strains non-Markovian model that accounts for realistic immunity waning and cross-immunity, inspired by the case of SARS-CoV-2 variants. We show that mutants with increased contagiousness or with some immune escape abilities are more likely to invade the population. We also show that the timing of the introduction of mutant strain in the population is key because it is associated with the population’s immunisation status. Our results underline the importance of immune waning and non-equilibrium dynamics on infectious disease evolution.
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ISSN:0022-5193
1095-8541
1095-8541
DOI:10.1016/j.jtbi.2025.112140