Modelling gastrointestinal parasitism infection in a sheep flock over two reproductive seasons: in silico exploration and sensitivity analysis

• Published in: Parasitology Vol. 143; no. 12; pp. 1509 - 1531
• Main Authors: SACCAREAU, M., MORENO, C. R., KYRIAZAKIS, I., FAIVRE, R., BISHOP, S. C.
• Format: Journal Article
• Language: English
• Published: Cambridge, UK Cambridge University Press 01.10.2016
• Subjects: Animal genetics; Animal growth; Animals; Anthelmintics - therapeutic use; Antiparasitic agents; Computer Science; Genetics; Genotype; Host-Parasite Interactions; Intestinal Diseases, Parasitic - parasitology; Intestinal Diseases, Parasitic - veterinary; Lactation; Life Sciences; Mathematics; Nematoda; Parasites; Parasitism; Reproduction; Sensitivity analysis; Sheep; Sheep Diseases - parasitology; Trichostrongyloidea - classification; Trichostrongyloidea - genetics; Trichostrongyloidea - isolation & purification; Trichostrongyloidiasis - parasitology; Trichostrongyloidiasis - veterinary; gastrointestinal parasitism; nutrition; genetic resistance; periparturient period; anthelmintics; dynamic model; sheep; anthelmintic
• ISSN: 0031-1820; 1469-8161
• DOI: 10.1017/S0031182016000871

In reproducing ewes, a periparturient breakdown of immunity is often observed to result in increased fecal egg excretion, making them the main source of infection for their immunologically naive lambs. In this study, we expanded a simulation model previously developed for growing lambs to explore the impact of the genotype (performance and resistance traits) and host nutrition on the performance and parasitism of both growing lambs and reproducing ewes naturally infected with Teladorsagia circumcincta. Our model accounted for nutrient-demanding phases, such as gestation and lactation, and included a supplementary module to manage the age structure of the ewe flock. The model was validated by comparison with published data. Because model parameters were unknown or poorly estimated, detailed sensitivity analysis of the model was performed for the sheep mortality and the level of infection, following a preliminary screening step. The parameters with the greatest effect on parasite-related outputs were those driving animal growth and milk yield. Our model enables different parasite-control strategies (host nutrition, breeding for resistance and anthelmintic treatments) to be assessed on the long term in a sheep flock. To optimize in silico exploration, the parameters highlighted by the sensitivity analysis should be refined with real data.