Dynamic model reveals interactions of viral strains and immunity levels in populations, suggesting new insights.
We present and analyze a dynamic evolution-oriented model of the spread of SARS-CoV-2 in a (homogeneous) population. Unlike previous such models, we use alleles at the various virus sites as our basic building blocks -- an approach that we find more natural and more effective in studying the evolution of viral strains. Our model parameters include: transmissibility, immunity levels, immunity waning rates, residual waned immunity levels, infection duration, mutation rates, epistasis, and possible antibody dependent enhancement. To compensate for the model complexity required for all of these features, we restrict to two virus sites with two alleles at each site, allowing us to explore how each of these features interacts with the basic evolutionary processes involved in viral strain changes. Our results show several qualitative patterns of interest in understanding viral strain dynamics, including founder effects of the seeded strain and an interplay between ease of evolution to neighboring strains and immune advantages of complementary strains. Overall, our allele-based approach uncovers insights about virus evolution, including the effects of parameter choices on the timing and patterns of the evolution of new strains, the staying power of the initial (seeded) strain, and the key roles that immunity plays.
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Koopman et al. (2025) studied this question.
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