Estimation of prevalence and incidence based on occurrence of health‐related events

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Abstract
A new method for estimating incidence and prevalence is developed, which only requires observation of occurrence of health‐related events within a given time window. Occurrence data are often easy to collect but estimating incidence and prevalence of a disease from such data is non‐trivial, since the true disease status is not directly observed for all at the beginning of the study period. Our method for overcoming this problem is based on an idea first presented in ‘The waiting time distribution as a graphical approach to epidemiologic measures of drug utilization’ (Epidemiology 1997; 8:666–670). Their fundamental idea is to analyse the waiting time from start of the window to the first event of each individual, and we formalize this by establishing a parametric likelihood which allows ordinary maximum likelihood analysis and explicit modelling of censoring. The developed method is used to analyse incidence and prevalence of hypertension in a Danish cohort of 70+‐year‐olds. A simulation study on the finite sample properties of the method is reported, which indicates that the method gives a quite robust and cost‐effective alternative to ordinary surveys and follow‐up studies for estimating incidence and prevalence. Copyright © 2005 John Wiley & Sons, Ltd.

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