title: Modelling macroparasite aggregation using a nematode-sheep system: the Weibull distribution as an alternative to the negative binomial distribution?
abstract: Macroparasites are almost always aggregated across their host populations, hence the Negative Binomial Distribution (NBD) with its exponent parameter k is widely used for modelling, quantifying or analysing parasite distributions. However, many studies have pointed out some drawbacks in the use of the NBD, with respect to the sensitivity of k to the mean number of parasites per host or the under-representation of the heavily infected hosts in the estimate of k. In this study, we compare the fit of the NBD with 4 other widely used distributions on observed parasitic gastrointestinal nematode distributions in their sheep host populations (11 datasets). Distributions were fitted to observed data using maximum likelihood estimator and the best fits were selected using the Akaike's Information Criterion (AIC). A simulation study was also conducted in order to assess the possible bias in parameter estimations especially in the case of small sample sizes. We found that the NBD is seldom the best fit for gastrointestinal nematode distributions. The Weibull distribution was clearly more appropriate over a very wide range of degrees of aggregation, mainly because it was more flexible in fitting the heavily infected hosts. Moreover, the Weibull distribution estimates are less sensitive to sample size. Thus, when possible, we suggest to carefully check on observed data if the NBD is appropriate before conducting any further analysis on parasite distributions.
authors.affiliation: INRA-Unité de Biométrie (UR 546), Domaine Saint Paul-Site Agroparc, 84814 Avignon cedex 9, France.
authors.forename: S
authors.initials: S
authors.lastname: Gaba
authors.forename: V
authors.initials: V
authors.lastname: Ginot
authors.forename: J
authors.initials: J
authors.lastname: Cabaret
mesh_terms: D000818:Animals; D008954:Models, Biological; D015233:Models, Statistical; D012756:Sheep; D012757:Sheep Diseases / Q000469:parasitology*; D014251:Trichostrongyloidea / Q000502:physiology*; D014252:Trichostrongyloidiasis / Q000469:parasitology / Q000662:veterinary*