Patterns of macroparasite aggregation in wildlife host populations

Frequency distributions from 49 published wildlife host-macroparasite syste ms were analysed by maximum likelihood for goodness of fit to the negative binomial distribution. In 45 of the 49 (90 %) data-sets, the negative binom ial distribution provided a statistically satisfactory fit. In the other 4 data-sets the negative binomial distribution still provided a better fit th an the Poisson distribution, and only 1 of the data-sets fitted the Poisson distribution. The degree of aggregation was large, with 43 of the 49 data- sets having an estimated k of less than 1 From these 19 data-sets, 22 subse ts of host data were available (i.e. host data could be divided by either h ost sex, age, where or when hosts were sampled). In 11 of these 22 subsets there was significant variation in the degree of aggregation between host s ubsets of the same host-parasite system. A common k estimate was always lar ger than that obtained with all the host data considered together. These re sults indicate that lumping host data can hide important variations in aggr egation between hosts and can exaggerate the true degree of aggregation. Wh erever possible common k estimates should be used to estimate the degree of aggregation. In addition, significant differences in the degree of aggrega tion between subgroups of host data, were generally associated with signifi cant differences in both mean parasite burdens and the prevalence of infect ion.