Precision of incidence predictions based on Poisson distributed observations.
Disease incidence predictions are useful for a number of administrative and scientific purposes. The simplest ones are made using trend extrapolation, on either an arithmetic or a logarithmic scale. This paper shows how approximate confidence prediction intervals can be calculated 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 for prediction models, for example, using power families and extra-Poisson variation, are also presented. Cancer incidence predictions for the Stockholm-Gotland Oncological Region in Sweden are used as an example.
Hakulinen
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Finnish Cancer Registry, Helsinki.
Dyba
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D000328:Adult; D000367:Age Factors; D016001:Confidence Intervals; D005260:Female; D005544:Forecasting; D006801:Humans; D015994:Incidence; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000453:epidemiology*; D016012:Poisson Distribution; D018709:Statistics, Nonparametric; D013548:Sweden / Q000453:epidemiology