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Gyro-scope: An individual-based computer model to forecast gyrodactylid infections on fish hosts

Wright, H.; Cable, J.; Potter, R.; van Oosterhout, C.


H. Wright

J. Cable

R. Potter

C. van Oosterhout


Individual-based computer models (IBM) feature prominently in current theoretical ecology but have only been applied in a small number of parasitological studies. Here we designed an IBM to simulate the infection dynamics of gyrodactylid parasites and immune defence of naïve hosts (i.e. fish previously not exposed to these parasites). We compared the results of the model with empirical data from guppies (Poecilia reticulata) infected with Gyrodactylus parasites. The laboratory experiments on guppies showed that larger fish acquired a heavier parasite load at the peak of the infection. The survival probability declined with increased body size and no fish survived a parasite load of 80 or more worms in this experiment (i.e. lethal load). The model was a good predictor of the Gyrodactylus infection dynamics of guppies and the model output was congruent with previously published data on Gyrodactylus salaris infections of salmon (Salmo salar). Computer simulations indicated that the infections persisted longer on larger hosts and that the parasite load increased exponentially with the body size of the host. Simulations furthermore predicted that the parasite load of fish with a standard length in excess of 17 mm (i.e. the size of adult guppies) reached a lethal load. This suggests that in the conditions of the experiment, the immune defence of naïve guppies can offer moderate protection against gyrodactylid infections to juveniles, but not to naïve adult guppies. The model is a useful tool to forecast the development of gyrodactylid infections on single hosts and make predictions about optimal life history strategies of parasites.


Wright, H., Cable, J., Potter, R., & van Oosterhout, C. (2008). Gyro-scope: An individual-based computer model to forecast gyrodactylid infections on fish hosts. International journal for parasitology, 38(5), 541-548. doi:10.1016/j.ijpara.2007.09.016

Journal Article Type Article
Acceptance Date Sep 18, 2007
Online Publication Date Oct 14, 2007
Publication Date 2008-04
Deposit Date Nov 13, 2014
Journal International Journal For Parasitology
Print ISSN 0020-7519
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 38
Issue 5
Pages 541-548
Keywords Parasitology; Infectious Diseases
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