  Negative binomial distribution is the most used distribution to model
macro-parasite burden in hosts. However reliable maximum likelihood parameter
estimation from data is far from trivial. No closed formula is available and
numerical estimation requires sophisticated methods. Using data from the
literature we show that simple alternatives to negative binomial, like
zero-inflated geometric or hurdle geometric distributions, produce a good and
even better fit to data than negative binomial distribution. We derived closed
simple formulas for the maximum likelihood parameter estimation which
constitutes a significant advantage of these distributions over negative
binomial distribution.
