When a predator avoids infected prey: a model-based theoretical study

M. Haque, D. Greenhalgh

Research output: Contribution to journalArticle

30 Citations (Scopus)

Abstract

In this paper we study a predator-prey model with logistic growth in the prey population, where a disease spreads among the prey according to an susceptible-infected-susceptible (SIS) epidemic model. The predators do not consume infected prey. After a review of the literature we formulate the basic mathematical model. For simplicity, we work initially with a model involving the fractions of prey susceptible and infected and then translate the results back to the model with absolute numbers. Both local and global stability results are examined. For the model working with absolute numbers, we find six possible equilibria and three important threshold values determining the behaviour of the system. There is always a unique locally stable equilibrium. We make conjectures concerning the global behaviour of the system. Next the effect of predator removal on the ecoepidemiological system is examined. The penultimate section describes numerical simulations using realistic parameter values for a real-life situation. This is humans predating on fish (Atlantic cod) infected by bacterial fin rot. The simulations confirm our conjectures. A discussion concludes the paper.
LanguageEnglish
Pages75-94
Number of pages19
JournalMathematical Medicine and Biology
Volume27
Issue number1
DOIs
Publication statusPublished - 2010

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Gadus morhua
Predator
Prey
theoretical study
Fishes
Theoretical Models
Logistic Models
predator
Model-based
predators
Growth
Population
Logistic Growth
Predator-prey Model
Epidemic Model
Local Stability
Fish
Global Stability
Threshold Value
disease spread

Keywords

  • ecoepidemiological model predator-prey system susceptible-infected-susceptible epidemic model disease equilibrium and stability analysis

Cite this

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When a predator avoids infected prey: a model-based theoretical study. / Haque, M.; Greenhalgh, D.

In: Mathematical Medicine and Biology, Vol. 27, No. 1, 2010, p. 75-94.

Research output: Contribution to journalArticle

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