title: A stochastic model accommodating the FAMACHA© system for estimating worm burdens and associated risk factors in sheep naturally infected with Haemonchus contortus.
abstract: A previously developed multiple regression algorithm was used as the basis of a stochastic model to simulate worm burdens in sheep naturally infected with Haemonchus contortus over five consecutive Haemonchus seasons (November to January/February) on a farm in the summer rainfall region in South Africa, although only one season is discussed. The algorithm associates haemoglobin levels with worm counts in individual animals. Variables were represented by distributions based on FAMACHA(©) scores and body weights of sheep, and Monte Carlo sampling was used to simulate worm burdens. Under conditions of high disease risk, defined as the sampling event during the worm season with the lowest relative mean haemoglobin level for a class of sheep, the model provided a distribution function for mean class H. contortus burdens and the probability of these occurring. A mean H. contortus burden for ewes (n=130 per sample) of approximately 1000 (range 51-28,768) and 2933 (range 78-44,175) for rams (n=120 per sample) was predicted under these conditions. At the beginning of the worm season when the risk of disease was lowest (i.e. when both classes had their highest estimated mean haemoglobin levels), a mean worm burden of 525 (range 39-4910) for ewes and 651 (range 37-17,260) for rams was predicted. Model indications were that despite being selectively drenched according to FAMACHA(©) evaluation, 72% of the ewes would maintain their mean worm burden below an arbitrarily selected threshold of 1000 even when risk of disease was at its highest. In contrast, far fewer rams (27%) remained below this threshold, especially towards the end of the worm season. The model was most sensitive to changes in haemoglobin value, and thus by extrapolation, the haematocrit, which is used as the gold standard for validating the FAMACHA(©) system. The mean class haemoglobin level at which there was a 50% probability of worm burdens being ≤ 1000 worms was 7.05 g/dl in ewes and 7.92 g/dl in rams.
authors.affiliation: Department of Veterinary Tropical Diseases, Faculty of Veterinary Science, University of Pretoria, Private Bag X04, 0110 Onderstepoort, South Africa.
authors.forename: D P
authors.initials: DP
authors.lastname: Reynecke
authors.forename: J A
authors.initials: JA
authors.lastname: Van Wyk
authors.forename: B
authors.initials: B
authors.lastname: Gummow
authors.forename: P
authors.initials: P
authors.lastname: Dorny
authors.forename: J
authors.initials: J
authors.lastname: Boomker
mesh_terms: D000818:Animals; D003198:Computer Simulation; D005243:Feces / Q000469:parasitology; D005260:Female; D005767:Gastrointestinal Diseases / Q000469:parasitology / Q000662:veterinary*; D006188:Haemonchiasis / Q000469:parasitology / Q000662:veterinary*; D006189:Haemonchus / Q000254:growth & development*; D006400:Hematocrit / Q000662:veterinary; D006454:Hemoglobins / Q000032:analysis; D008297:Male; D015233:Models, Statistical; D010270:Parasite Egg Count / Q000662:veterinary; D018570:Risk Assessment / Q000379:methods; D012756:Sheep; D012757:Sheep Diseases / Q000469:parasitology*; D013019:South Africa
chemical_list: D006454:Hemoglobins