The Use of Capture-Recapture Models in Epidemiological Surveillance
by Anne Chao
Abstract: Capture-recapture methodology, originally developed for estimating demographic parameters of animal populations, has been applied to human populations. This talk reviews various closed capture-recapture models which are applicable to ascertainment data for estimating the size of a target population based on several incomplete lists of individuals. Most epidemiological approaches merging different lists and eliminating duplicate cases are likely to be biased downwards. That is, the final merged list miss those who are in the population but were not ascertained in any of the lists. If there are no matching errors, then the duplicate information collected from a capture-recapture experiment can be used to estimate the number of missed under proper assumptions. Three approaches and their associated estimation procedures are introduced: ecological models, log-linear models, and the sample coverage approach. Each approach has its unique way of incorporating two types of source dependencies: local (list) dependence and dependence due to heterogeneity. An interactive program, CARE (for capture-recapture) developed by Chao et al. is introduced using several real data sets, which provide examples to show the usefulness of the capture-recapture method in correcting for under-ascertainment. The limitations of the methodology and some cautionary remarks are also discussed.
The lecture will run for 2 hours.
For More Information: Richard Huggins, R.Huggins@ms.unimelb.edu.au