Print PageIt is well known that parasites are often highly aggregated on their hosts such that relatively few individuals host the large majority of parasites. The cause of this aggregation, however, is much less clear, especially for parasites such as arthropod vectors, which generally spend only a short time on their hosts. Using blacklegged ticks (Ixodes scapularis) on mice (Peromyscus leucopus) as a motivating example, we present a simple model of vector accumulation and loss on hosts, built from first principles, and then show how an approximately negative binomial distribution of vector burdens can be derived from reasonable assumptions on how questing vector densities and host movement rates vary among hosts. We then fit the model to several datasets of larval tick burdens using a hierarchical Bayesian framework.
Results/Conclusions
Our model is able to explain the extreme observed aggregation of tick burdens on mice without invoking any intrinsic differences among them. Our results suggest that the reason some mice harbor such large burdens is simply bad luck.
