Abstract
We consider a stochastic model for an evolving population. We show that in the presence of genotype extinctions the population dies out for a low mutation probability but may survive for a high mutation probability. This turns upside down the widely held belief that above a certain mutation threshold a population cannot survive.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Nowak, M.A., May, R.M.: Virus Dynamics. Oxford University Press, Oxford (2000)
Eigen, M.: Error catastrophe and antiviral strategy. PNAS 99, 13374–13376 (2002)
Manrubia, S.C., Domingo, E., Lazaro, E.: Pathways to extinction: beyond the error threshold. Phil. Trans. R. Soc. B 365, 1943–1952 (2010)
Mayr, E.: What Evolution Is. Basic Books, New York (2001)
Cox, J.T., Schinazi, R.B.: A branching process for virus survival. J. Appl. Probab. 49, 888–894 (2012)
Schinazi, R.B., Schweinsberg, J.: Spatial and non spatial stochastic models for immune response. Markov Process. Relat. Fields 14, 255–276 (2008)
Schinazi, R.B.: Classical and Spatial Stochastic Processes, 2nd edn. Birkhauser, New York (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Schinazi, R.B. (2019). Survival Under High Mutation. In: Giacomin, G., Olla, S., Saada, E., Spohn, H., Stoltz, G. (eds) Stochastic Dynamics Out of Equilibrium. IHPStochDyn 2017. Springer Proceedings in Mathematics & Statistics, vol 282. Springer, Cham. https://doi.org/10.1007/978-3-030-15096-9_14
Download citation
DOI: https://doi.org/10.1007/978-3-030-15096-9_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-15095-2
Online ISBN: 978-3-030-15096-9
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)