Skip to main content
Log in

Superinfections can induce evolutionarily stable coexistence of pathogens

  • Published:
Journal of Mathematical Biology Aims and scope Submit manuscript

Abstract

Parasites reproduce and are subject to natural selection at several different, but intertwined, levels. In the recent paper, Gilchrist and Coombs (Theor. Popul. Biol. 69:145–153, 2006) relate the between-host transmission in the context of an SI model to the dynamics within a host. They demonstrate that within-host selection may lead to an outcome that differs from the outcome of selection at the host population level. In this paper we combine the two levels of reproduction by considering the possibility of superinfection and study the evolution of the pathogen’s within-host reproduction rate p. We introduce a superinfection function φ = φ(p,q), giving the probability with which pathogens with trait q, upon transmission to a host that is already infected by pathogens with trait p, “take over” the host. We consider three cases according to whether the function q → φ(p,q) (i) has a discontinuity, (ii) is continuous, but not differentiable, or (iii) is differentiable in q = p. We find that in case (i) the within-host selection dominates in the sense that the outcome of evolution at the host population level coincides with the outcome of evolution in a single infected host. In case (iii), it is the transmission to susceptible hosts that dominates the evolution to the extent that the singular strategies are the same as when the possibility of superinfections is ignored. In the biologically most relevant case (ii), both forms of reproduction contribute to the value of a singular trait. We show that when φ is derived from a branching process variant of the submodel for the within-host interaction of pathogens and target cells, the superinfection functions fall under case (ii). We furthermore demonstrate that the superinfection model allows for steady coexistence of pathogen traits at the host population level, both on the ecological, as well as on the evolutionary time scale.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Alizon, S.: Parasite virulence evolution: insights from embedded models. PhD thesis, University of Paris, France (2006)

  2. Alizon S. and Baalen M. (2005). Emergence of a convex trade-off between transmission and virulence. Am. Nat. 165: 155–167

    Article  Google Scholar 

  3. Anderson R.M. and May R.M. (1982). Coevolution of hosts and parasites. Parasitology 85: 411–426

    Google Scholar 

  4. Anderson R.M. and May R.M. (1991). Infectious Diseases of Humans: Dynamics and Control. Oxford University Press, Oxford

    Google Scholar 

  5. Antia R., Levin B.R. and May R.M. (1994). Within-host population dynamics and the evolution and maintenance of macroparasite virulence. Am. Nat. 144: 457–472

    Article  Google Scholar 

  6. Day T. and Proulx S.R. (2004). A general theory for the evolutionary dynamics of virulence. Am. Nat. 163: 40–63

    Article  Google Scholar 

  7. De Leenheer P. and Smith H.L. (2003). Virus dynamics: a global analysis. SIAM J. Appl. Math. 63(4): 1313–1327

    Article  MATH  MathSciNet  Google Scholar 

  8. Dieckmann U. and Metz J.A.J. (2006). Surprising evolutionary predictions from enhanced ecological realism. Theor. Popul. Biol. 69(3): 263–281

    Article  MATH  Google Scholar 

  9. Dieckmann, U., Metz, J.A.J., Sabelis, M.W., Sigmund, K.: Adaptive Dynamics of Infectious Diseases: In Pursuit of Virulence Management. Cambridge Studies in Adaptive Dynamics, Cambridge University Press, Cambridge (2002)

  10. Diekmann, O.: A beginner’s guide to adaptive dynamics. In: Mathematical Modelling of Population Dynamics of Banach Center Publ., vol. 63, pp. 47–86. Polish Acad. Sci., Warsaw (2004)

  11. Diekmann O., Gyllenberg M. and Metz J.A.J. (2003). Steady-state analysis of structured population models. Theor. Popul. Biol. 63(4): 309–338

    Article  MATH  Google Scholar 

  12. Diekmann, O., Heesterbeek, J.A.P.: Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation. Wiley Series in Mathematical and Computational Biology. Wiley, Chichester (2000)

  13. Ewald P.W. (1983). Host–parasite relations, vectors and the evolution of disease severity. Ann. Rev. Ecol. Syst. 14: 465–485

    Article  Google Scholar 

  14. Ewald P.W. (1994). Evolution of Infectious Disease. Oxford University Press, Oxford

    Google Scholar 

  15. Ganusov V.V. and Antia R. (2003). Trade-offs and the evolution of virulence of microparasites: do details matter? Theor. Popul. Biol. 64(2): 211–220

    Article  MATH  MathSciNet  Google Scholar 

  16. Geritz S.A.H. (2005). Resident-invader dynamics and the coexistence of similar strategies. J. Math. Biol. 50(1): 67–82

    Article  MATH  MathSciNet  Google Scholar 

  17. Geritz S.A.H., Gyllenberg M., Jacobs F.J.A. and Parvinen K. (2002). Invasion dynamics and attractor inheritance. J. Math. Biol. 44: 548–560

    Article  MATH  MathSciNet  Google Scholar 

  18. Geritz S.A.H., Kisdi E., Meszena G. and Metz J.A.J. (1998). Evolutionary singular strategies and the adaptive growth and branching of the evolutionary tree. Evol. Ecol. 12: 35–57

    Article  Google Scholar 

  19. Gilchrist M.A. and Coombs D. (2006). Evolution of virulence: interdependence, constraints and selection using nested models. Theor. Popul. Biol. 69: 145–153

    Article  MATH  Google Scholar 

  20. Gomes, G.M., Medley, G.F.: Dynamics of multiple strains of infectious agents coupled by cross-immunity: a comparison of models. In: Castillo-Chavez, C., et al. (eds.) Mathematical Approaches for Emerging and Reemerging Infectious Diseases: Models, Methods, and Theory. Proceedings of a Workshop, Integral part of the IMA Program on Mathematics in Biology. IMA Vol. Math. Appl. 126, pp. 171–191. Springer, New York (2002)

  21. Grenfell B.T., Pybus O.G., Gog J.R., Wood J.L.N., Daly J.M., Mumford J.A. and Holmes E.C. (2004). Unifying the epidemiological and evolutionary dynamics of pathogens. Science 303: 327–332

    Article  Google Scholar 

  22. Haccou, P., Jagers, P., Vatutin, V.A.: Branching Processes: Variation, Growth, and Extinction of Populations. Cambridge Studies in Adaptive Dynamics. Cambridge University Press, Cambridge (2005)

  23. Hochberg M.E. and Holt R.D. (1990). The coexistence of competing parasites. I. The role of cross-species infection. Am. Nat. 136: 517–541

    Article  Google Scholar 

  24. Klinkenberg D. and Heesterbeek J.A.P. (2005). A simple model for the within-host dynamics of a protozoan parasite. Proc. Roy. Soc. B 272: 593–600

    Article  Google Scholar 

  25. Lenski R.E. and May R.M. (1994). The evolution of virulence in parasites and pathogens: reconciliation between the competing hypotheses. J. Theor. Biol. 169: 253–265

    Article  Google Scholar 

  26. Levin, S.A.: Coevolution. In: Freedman H., Strobeck C. (eds.) Population Biology. Lecture notes in Biomathematics 52, pp. 328–334 (1983)

  27. Levin, S.A.: Some approaches to the modelling of coevolutionary interactions. In: Nitecki M. (ed.) Coevolution, pp. 21–65 (1983)

  28. Levin S.A. and Pimentel D. (1981). Selection of intermediate rates of increase in parasite-host systems. Am. Nat. 117: 308–315

    Article  MathSciNet  Google Scholar 

  29. Matessi C. and Di Pasquale C. (1996). Long-term evolution of multilocus traits. J. Math. Biol. 34: 613–653

    MATH  Google Scholar 

  30. May R.M. and Anderson R.M. (1983). Epidemiology and genetics in the coevolution of parasites and hosts. Proc. Roy. Soc. Lond. B 219: 281–313

    Article  MATH  Google Scholar 

  31. Metz, J.A.J., Geritz, S.A.H., Meszéna, G., Jacobs, F.J.A., van Heerwaarden, J.S.: Adaptive dynamics, a geometrical study of the consequences of nearly faithful reproduction. In: van Strien, S.J., et al. (eds.) Stochastic and spatial structures of dynamical systems. Proceedings of the Meeting, Amsterdam, Netherlands, January 1995. Verh. Afd. Natuurkd., Amsterdam, 1. Reeks, K. Ned. Akad. Wet. 45, pp. 183–231 (1996)

  32. Metz, J.A.J., Mylius, S.D., Diekmann, O.: When does evolution optimise? On the relation between types of density dependence and evolutionarily stable life histories. IIASA working paper WP-96-04, (1996). http://www.iiasa.ac.at/cgi-bin/pubsrch?WP96004

  33. Meyers L.A., Levin B.R., Richardson A.R. and Stojiljkovic I. (2003). Epidemiology, hypermutation, within-host evolution and the virulence of neisseria meningitidis. Proc. Roy. Soc. Lond. B 270: 1667–1677

    Article  Google Scholar 

  34. Mosquera J. and Adler F.R. (1998). Evolution of virulence: a unified framework for coinfection and superinfection. J. Theor. Biol. 195: 293–313

    Article  Google Scholar 

  35. Murase A., Sasaki T. and Kajiwara T. (2005). Stability analysis of pathogen-immune interaction dynamics. J. Math. Biol. 51(3): 247–267

    Article  MATH  MathSciNet  Google Scholar 

  36. Mylius S.D. and Diekmann O. (1995). On evolutionarily stable life histories, optimization and the need to be specific about density dependence. Oikos 74: 218–224

    Article  Google Scholar 

  37. Nowak M.A. and May R.M. (1994). Superinfection and the evolution of parasite virulence. Proc. Roy. Soc. Lond. B 255: 81–89

    Article  Google Scholar 

  38. Nowak M.A. and May R.M. (2000). Virus Dynamics: Mathematical Principles of Immunology and Virology. Oxford University Press, Oxford

    MATH  Google Scholar 

  39. Perelson A.S., Kirschner D.E. and Boer R. (1993). Dynamics of HIV infection of CD4+ T cells. Math. Biosci. 114(1): 81–125

    Article  MATH  Google Scholar 

  40. Pugliese, A.: Evolutionary dynamics of virulence. Available online at: http://www.science.unitn.it/pugliese/

  41. Pugliese A. (2002). On the evolutionary coexistence of parasite strains. Math. Biosci. 177/178: 355–375

    Article  MathSciNet  Google Scholar 

  42. Saldaña J., Elena S.F. and Solé R.V. (2003). Coinfection and superinfection in RNA virus population: a selection-mutation model. Math. Biosci. 183: 135–160

    Article  MATH  MathSciNet  Google Scholar 

  43. Smith V.H. and Holt R.D. (1996). Resource competition and within-host disease dynamics. Tree 11: 386–389

    Google Scholar 

  44. Thieme, H.R.: Pathogen competition and coexistence and the evolution of virulence. In: Mathematics for Life Sciences and Medicine. Springer, Heidelberg (2007, in press)

  45. van Baalen M. and Sabelis M.W. (1995). The milker-killer dilemma and spatially structured predator-prey interactions. Oikos 74: 391–400

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Barbara Boldin.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Boldin, B., Diekmann, O. Superinfections can induce evolutionarily stable coexistence of pathogens. J. Math. Biol. 56, 635–672 (2008). https://doi.org/10.1007/s00285-007-0135-1

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00285-007-0135-1

Keywords

Mathematics Subject Classification (2000)

Navigation