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Ecological interference between fatal diseases

Abstract

An important issue in population biology is the dynamic interaction between pathogens. Interest has focused mainly on the indirect interaction of pathogen strains, mediated by cross immunity1,2,3,4. However, a mechanism has recently been proposed for ‘ecological interference’ between pathogens through the removal of individuals from the susceptible pool after an acute infection. To explore this possibility, we have analysed and modelled historical measles and whooping cough records. Here we show that ecological interference is particularly strong when fatal infections permanently remove susceptibles. Disease interference has substantial dynamical consequences, making multi-annual outbreaks of different infections characteristically out of phase. So, when disease prevalence is high and is associated with significant mortality, it might be impossible to understand epidemic patterns by studying pathogens in isolation. This new ecological null model has important consequences for understanding the multi-strain dynamics of pathogens such as dengue and echoviruses.

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Figure 1: Analysis of the two-disease model dynamics.
Figure 2: Weekly case fatality reports for measles (black) and whooping cough (grey) in five European cities.
Figure 3: Temporal synchrony of strains, produced by a stochastic three-disease model.

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References

  1. Gog, J. R. & Swinton, J. A. A status-based approach to multiple strain dynamics. J. Math. Biol. 44, 169–184 (2002)

    Article  MathSciNet  CAS  PubMed  Google Scholar 

  2. Gupta, S., Ferguson, N. M. & Anderson, R. M. Chaos, persistence and evolution of strain structure in antigenically diverse infectious agents. Science 280, 912–915 (1998)

    Article  ADS  CAS  PubMed  Google Scholar 

  3. Gomes, M. G. M., Medley, G. F. & Nokes, D. J. On the determinants of population structure in antigenically diverse pathogens. Proc. R. Soc. Lond. B 269, 227–233 (2002)

    Article  Google Scholar 

  4. Dietz, K. Epidemiologic interference of virus populations. J. Math. Biol. 8, 291–300 (1979)

    Article  MathSciNet  CAS  PubMed  Google Scholar 

  5. Creighton, C. A History of Epidemics in Britain (Cambridge Univ. Press, Cambridge, 1894)

    Google Scholar 

  6. Rohani, P., Earn, D. J. D., Finkenstadt, B. F. & Grenfell, B. T. Population dynamic interference among childhood diseases. Proc. R. Soc. Lond. B 265, 2033–2041 (1998)

    Article  CAS  Google Scholar 

  7. Anderson, R. M. & May, R. M. Infectious Diseases of Humans: Dynamics and Control (Oxford Univ. Press, Oxford, 1991)

    Google Scholar 

  8. Earn, D. J. D., Rohani, P., Bolker, B. M. & Grenfell, B. T. A simple model for complex dynamical transitions in epidemics. Science 287, 667–670 (2000)

    Article  ADS  CAS  PubMed  Google Scholar 

  9. Rand, D. A. & Wilson, H. B. Chaotic stochasticity: a ubiquitous source of unpredictability in epidemics. Proc. R. Soc. Lond. B 246, 179–184 (1991)

    Article  ADS  CAS  Google Scholar 

  10. McLean, A. & Anderson, R. Measles in developing countries part I. Epidemiological parameters and patterns. Epidemiol. Infect. 100, 111–133 (1988)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Anderson, R. M. & May, R. M. Directly transmitted infectious diseases: control by vaccination. Science 215, 1053–1060 (1982)

    Article  ADS  MathSciNet  CAS  PubMed  Google Scholar 

  12. Schenzle, D. An age-structured model of pre- and post-vaccination measles transmission. IMA J. Math. Appl. Med. Biol. 1, 169–191 (1984)

    Article  MathSciNet  CAS  PubMed  Google Scholar 

  13. Rohani, P., Earn, D. J. D. & Grenfell, B. T. Opposite patterns of synchrony in sympatric disease metapopulations. Science 286, 968–971 (1999)

    Article  CAS  PubMed  Google Scholar 

  14. Butler, W. Measles. Proc. R. Soc. Med. 6, 120–153 (1913)

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Kamo, M. & Sasaki, A. The effects of cross-immunity and seasonal forcing in a multi-strain epidemic model. Physica D 165, 228–241 (2002)

    Article  ADS  Google Scholar 

  16. Wenjie, W. Control of dengue/dengue haemorrhagic fever in china. Dengue Bull. 21http://w3.whosea.org/DengueBulletin21/ch3f.htm〉 (1997)

  17. Focks, D. A., Brenner, R. J., Hayes, J. & Daniels, E. Transmission thresholds for dengue in terms of Aedes aegypti pupae per person with discussion of their utility in source. Am. J. Trop. Med. Hyg. 62, 11–18 (2000)

    Article  CAS  PubMed  Google Scholar 

  18. Hales, S., de Wet, N., Maindonald, J. & Woodward, A. Potential effect of population and climate changes on global distribution of dengue fever: an empirical model. Lancet 360, 830–834 (2002)

    Article  PubMed  Google Scholar 

  19. Kurane, I., Mady, B. J. & Ennis, F. A. Antibody-dependent enhancement of dengue virus infection. Rev. Med. Virol. 1, 211–222 (1991)

    Article  Google Scholar 

  20. Behrman, R. E. & Kliegman, R. M. Nelson Essentials of Pediatrics (Saunders, Philadelphia, 1998)

    Google Scholar 

  21. Cherry, J. D. Pertussis in adults. Ann. Intern. Med. 128, 64–66 (1998)

    Article  CAS  PubMed  Google Scholar 

  22. Miller, E. & Gay, N. Epidemiological determinants of pertussis. Dev. Biol. Stand. 89, 15–23 (1997)

    CAS  PubMed  Google Scholar 

  23. Keeling, M. J., Rohani, P. & Grenfell, B. T. Seasonally forced disease dynamics explored as switching between attractors. Physica D 148, 317–335 (2001)

    Article  ADS  Google Scholar 

  24. Butler, W. Whooping cough and measles. Proc. R. Soc. Med. 40, 384–398 (1947)

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Bartlett, M. S. Measles periodicity and community size. J. R. Stat. Soc. 1, 48–59 (1957)

    Google Scholar 

  26. Soper, H. E. The interpretation of periodicity in disease prevalence. J. R. Stat. Soc. 92, 34–73 (1929)

    Article  Google Scholar 

  27. Linnert, L. A statistical report on measles notifications in Manchester, 1917–1951. (Department of Mathematical Statistics, Manchester, UK, 1954)

    Google Scholar 

  28. Grenfell, B. T., Bjornstad, O. N. & Kappey, J. Travelling waves and spatial hierarchies in measles epidemics. Nature 414, 716–723 (2001)

    Article  ADS  CAS  PubMed  Google Scholar 

  29. Torrence, C. & Compo, G. P. A practical guide to wavelet analysis. Bull. Am. Meteorol. Soc. 79, 61–78 (1998)

    Article  ADS  Google Scholar 

  30. Buonaccorsi, J. P., Elkington, J. S., Evans, S. R. & Liebhold, A. M. Measuring and testing for spatial synchrony. Ecology 82, 1668–1679 (2001)

    Article  Google Scholar 

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Acknowledgements

We thank O. Bjornstad, M. Boots, D. Gubler and H. Wearing for comments on this manuscript.

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Correspondence to P. Rohani.

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The authors declare that they have no competing financial interests.

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Rohani, P., Green, C., Mantilla-Beniers, N. et al. Ecological interference between fatal diseases. Nature 422, 885–888 (2003). https://doi.org/10.1038/nature01542

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