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Eco-evolutionary constraints for the endemicity of rapidly evolving viruses (2411.02097v1)

Published 4 Nov 2024 in q-bio.PE and physics.soc-ph

Abstract: Antigenic escape constitutes the main mechanism allowing rapidly evolving viruses to achieve endemicity. Beyond granting immune escape, empirical evidence also suggests that mutations of viruses might increase their inter-host transmissibility. While both mechanisms are well-studied individually, their combined effects on viral endemicity remain to be explored. Here we propose a minimal eco-evolutionary framework to simulate epidemic outbreaks generated by pathogens evolving both their transmissibility and immune escape. Our findings uncover a very rich phenomenology arising from the complex interplay between both evolutionary pathways and the underlying contagion dynamics. We first show that contagions at the population level constrain the effective evolution of the virus, accelerating the increase in transmissibility in the first epidemic wave while favoring antigenic variation in the transition to the endemic phase. Our results also reveal that accounting for both evolutionary pathways changes the features of the viruses more prone to become endemic. While chances for endemicity increase with infectiousness of the wild-type variant for viruses not evolving their transmissibility, a non-monotonic behavior is observed when the latter mechanism is included, favoring less transmissible viruses and impairing those ones with intermediate infectiousness.

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References (26)
  1. A. Moya, E. C. Holmes, and F. González-Candelas, The population genetics and evolutionary epidemiology of rna viruses, Nature Reviews Microbiology 2, 279 (2004).
  2. M. J. Keeling and P. Rohani, Modeling infectious diseases in humans and animals (Princeton university press, 2011).
  3. A. P. Galvani, Epidemiology meets evolutionary ecology, Trends in Ecology & Evolution 18, 132 (2003).
  4. C. E. Van de Sandt, J. H. Kreijtz, and G. F. Rimmelzwaan, Evasion of influenza a viruses from innate and adaptive immune responses, Viruses 4, 1438 (2012).
  5. J. R. Gog and B. T. Grenfell, Dynamics and selection of many-strain pathogens, Proceedings of the National Academy of Sciences 99, 17209 (2002).
  6. K. Koelle, M. Kamradt, and M. Pascual, Understanding the dynamics of rapidly evolving pathogens through modeling the tempo of antigenic change: influenza as a case study, Epidemics 1, 129 (2009).
  7. I. Atienza-Diez and L. F. Seoane, Long-and short-term effects of cross-immunity in epidemic dynamics, Chaos, Solitons & Fractals 174, 113800 (2023).
  8. I. M. Rouzine and G. Rozhnova, Antigenic evolution of viruses in host populations, PLoS pathogens 14, e1007291 (2018).
  9. A. D. Stewart, J. M. Logsdon, and S. E. Kelley, An empirical study of the evolution of virulence under both horizontal and vertical transmission, Evolution 59, 730 (2005).
  10. B. A. Walther and P. W. Ewald, Pathogen survival in the external environment and the evolution of virulence, Biological Reviews 79, 849 (2004).
  11. S. T. Abedon, T. D. Herschler, and D. Stopar, Bacteriophage latent-period evolution as a response to resource availability, Applied and environmental microbiology 67, 4233 (2001).
  12. A. Sasaki, S. Lion, and M. Boots, Antigenic escape selects for the evolution of higher pathogen transmission and virulence, Nature ecology & evolution 6, 51 (2022).
  13. L. E. Cohen, D. J. Spiro, and C. Viboud, Projecting the sars-cov-2 transition from pandemicity to endemicity: Epidemiological and immunological considerations, PLoS Pathogens 18, e1010591 (2022).
  14. J. S. Lavine, O. N. Bjornstad, and R. Antia, Immunological characteristics govern the transition of covid-19 to endemicity, Science 371, 741 (2021).
  15. R. Antia and M. E. Halloran, Transition to endemicity: Understanding covid-19, Immunity 54, 2172 (2021).
  16. J. Wallinga and P. Teunis, Different epidemic curves for severe acute respiratory syndrome reveal similar impacts of control measures, American Journal of epidemiology 160, 509 (2004).
  17. S. Alizon, Transmission-recovery trade-offs to study parasite evolution, The American Naturalist 172, E113 (2008).
  18. M. Turkyilmazoglu, Explicit formulae for the peak time of an epidemic from the sir model, Physica D: Nonlinear Phenomena 422, 132902 (2021).
  19. L. S. Tsimring, H. Levine, and D. A. Kessler, Rna virus evolution via a fitness-space model, Physical review letters 76, 4440 (1996).
  20. O. A. van Herwaarden, Stochastic epidemics: the probability of extinction of an infectious disease at the end of a major outbreak, Journal of mathematical biology 35, 793 (1997).
  21. N. Perra, Non-pharmaceutical interventions during the covid-19 pandemic: A review, Physics Reports 913, 1 (2021).
  22. I. M. Rouzine and G. Rozhnova, Evolutionary implications of sars-cov-2 vaccination for the future design of vaccination strategies, Communications medicine 3, 86 (2023).
  23. S. Wright, Isolation by distance, Genetics 28, 114 (1943).
  24. G. Hess, Disease in metapopulation models: implications for conservation, Ecology 77, 1617 (1996).
  25. D. H. Goldhill and P. E. Turner, The evolution of life history trade-offs in viruses, Current opinion in virology 8, 79 (2014).
  26. R. M. Anderson and R. M. May, Coevolution of hosts and parasites, Parasitology 85, 411 (1982).

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