Stochastic and spatial dynamics of nematode parasites in farmed ruminants

Stephen J. Cornell, Valerie S. Isham, Bryan T. Grenfell

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

Host-parasite systems provide powerful opportunities for the study of spatial and stochastic effects in ecology; this has been particularly so for directly transmitted microparasites. Here, we construct a fully stochastic model of the population dynamics of a macroparasite system: trichostrongylid gastrointestinal nematode parasites of farmed ruminants. The model subsumes two implicit spatial effects: the host population size (the spatial extent of the interaction between hosts) and spatial heterogeneity ('clumping') in the infection process. This enables us to investigate the roles of several different processes in generating aggregated parasite distributions. The necessity for female worms to find a mate in order to reproduce leads to an Allee effect, which interacts nonlinearly with the stochastic population dynamics and leads to the counter-intuitive result that, when rare, epidemics can be more likely and more severe in small host populations. Clumping in the infection process reduces the strength of this Allee effect, but can hamper the spread of an epidemic by making infection events too rare. Heterogeneity in the hosts' response to infection has to be included in the model to generate aggregation at the level observed empirically.

Original languageEnglish (US)
Pages (from-to)1243-1250
Number of pages8
JournalProceedings of the Royal Society B: Biological Sciences
Volume271
Issue number1545
DOIs
StatePublished - Jun 22 2004
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General Immunology and Microbiology
  • General Environmental Science
  • General Biochemistry, Genetics and Molecular Biology
  • General Agricultural and Biological Sciences

Keywords

  • Aggregation
  • Allee effect
  • Heterogeneity
  • Parasite population dynamics
  • Spatial effects
  • Stochasticity

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