Copula function is a powerful tool for modelling the structural dependency of correlated continuous data. Dependent count discrete data arise in some area of spatial point pattern processes, which the counts are affected by the distance to some especial focus. For analysis of these points it is necessary to nd the corre- lation structure of counts and the distances to the special focuses. In this talk, by implementing the introducing of some events around to the especial focuses and identifying the properties of valid spatial point pattern copulas, the count-distance based data are modelled. Next, the proposed models were applied to predict the number of rats and cockroaches in some parts of Madrid. Afterwards, based on pair copula construction, the trivariate distribution for the number of rats, cockroaches and distances to focuses was constructed to predict the counts of events given by the other variables.
