PSXIV-18 Fit of the Zero-Inflated Negative Binomial Model to Analyze Fecal Egg Counts

Abstract

Abstract Fecal egg count (FEC) is used as an indicator of parasite infection level in sheep. The distribution of FEC is non-Gaussian and typically overdispersed, often with an excess in zero counts. Quantifying the extent of inflation of zero counts can be difficult. Our objective was to assess the potential zero-inflation problem in FEC resulting from variation in infection with gastrointestinal nematodes by using a generalized linear model approach. The zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) models are useful techniques to analyze count data with excess zeros; ZINB also handles overdispersion. The ZINB model has the potential to delineate ‘true’ zeros, in this case, animals resistant to parasitism and thereby with zero FEC, from ‘false’ zeros, animals never or minimally exposed to a parasite challenge. By distinguishing false zeros, those animals expressing parasite resistance may be more clearly identified. Two datasets on Katahdin sheep, a hair breed known to express resistance to gastrointestinal nematodes, were investigated; a smaller set (n = 3,048) with FEC and FAMACHA (FAM) scores, a subjective measure of anemia indicative of parasitism by Haemonchus contortus, a blood sucking helminth; and a larger set (n = 14,405) with FEC and a contemporary group (CG) designation, assigned based on the flock, birth year, management group, and FEC recording date of the animal. Among animals with FAM recorded, 14% had scores indicative of at least border line anemia. Amongst the 410 CG, 22% had mean FEC more than 500 egg/g, a threshold value routinely used to indicate a substantial infection level with H. contortus. For each dataset, the Poisson, Negative Binomial, ZIP, and ZINB models were fit and compared using R (pscl package) and SAS software, with the ZINB providing the best fit. In the models considered, FEC was the response variable and either FAM or CG was the explanatory variable, depending on the dataset. Despite evidence of parasite challenge, the true and false zeros could not be delineated in both data sets using these models. The estimated proportion of false zeros due to inflation did not differ from the proportion of zeros observed in the data set. Either all zeros coincided with no infection, which seems unlikely in Katahdins, or neither FAM nor CG provided sufficient information to distinguish resistant from uninfected individuals. Alternative or additional explanatory variables, such as packed cell volume or immunoglobulin concentrations indicative of parasitic infection, may be necessary to separate true from false zero FEC in sheep challenged with gastrointestinal nematodes using the ZINB model.