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Keywords:

  • avian malaria;
  • disease dynamics;
  • Haemosporidia;
  • vector-borne disease;
  • Haemoproteus

Summary

  • 1
    Seasonal variation in environmental conditions is ubiquitous and can affect the spread of infectious diseases. Understanding seasonal patterns of disease incidence can help to identify mechanisms, such as the demography of hosts and vectors, which influence parasite transmission dynamics.
  • 2
    We examined seasonal variation in Plasmodium infection in a blue tit Cyanistes caeruleus population over 3 years using sensitive molecular diagnostic techniques, in light of Beaudoin et al.'s (1971; Journal of Wildlife Diseases, 7, 5–13) model of seasonal variation in avian malaria prevalence in temperate areas. This model predicts a within-year bimodal pattern of spring and autumn peaks with a winter absence of infection.
  • 3
    Avian malaria infections were mostly Plasmodium (24·4%) with occasional Haemoproteus infections (0·8%). Statistical nonlinear smoothing techniques applied to longitudinal presence/absence data revealed marked temporal variation in Plasmodium prevalence, which apparently showed a within-year bimodal pattern similar to Beaudoin et al.'s model. However, of the two Plasmodium morphospecies accounting for most infections, only the seasonal pattern of Plasmodium circumflexum supported Beaudoin et al.'s model. On closer examination there was also considerable age structure in infection: Beaudoin et al.'s seasonal pattern was observed only in first year and not older birds. Plasmodium relictum prevalence was less seasonally variable.
  • 4
    For these two Plasmodium morphospecies, we reject Beaudoin et al.'s model as it does not survive closer scrutiny of the complexities of seasonal variation among Plasmodium morphospecies and host age classes. Studies of host–parasite interactions should consider seasonal variation whenever possible. We discuss the ecological and evolutionary implications of seasonal variation in disease prevalence.