PRECISION OF INCIDENCE PREDICTIONS BASED ON POISSON DISTRIBUTED OBSERVATIONS

Disease incidence predictions are useful for a number of administrativ e and scientific purposes. The simplest ones are made using trend extr apolation, on either an arithmetic or a logarithmic scale. This paper shows how approximate confidence prediction intervals can be calculate d for such predictions, both for the total number of cases and for the age-adjusted incidence rates, by assuming Poisson distribution of the age and period specific numbers of incident cases. Generalizations fo r prediction models, for example, using power families and extra-Poiss on variation, are also presented. Cancer incidence predictions for the Stockholm-Gotland Oncological Region in Sweden are used as an example .