The applications of capture‐recapture models to epidemiological data

Abstract

Capture-recapture methodology, originally developed for estimating demographic parameters of animal populations, has been applied to human populations. This tutorial 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 misses 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 the authors is demonstrated using four real data sets. One set of data deals with infection by the acute hepatitis A virus in an outbreak in Taiwan; the other three sets are ascertainment data on diabetes, spina bifida and infants' congenital anomaly discussed in the literature. These data sets 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.

Estimation of Cancer Cases Using Capture-Recapture Method in Northwest Iran

“…During recent years, a wide range of efforts has been conducted to design "cancer registry" systems (Doungchawee et al, 2002;Mousavi et al, 2008;Sadjadi et al, 2008;Zou et al, 2011). In this direction, to ensure the quality of gathered data, many methods have been developed in the recent years and capture-recapture is one of the most applicable methods (Chao et al, 2001;Behtash et al, 2006;Hajian et al, 2011).…”

Socioeconomic conditions and type 1 diabetes in childhood in North Rhine–Westphalia, Germany

“…Registration of cases by data sources is presented in Table 1. Completeness of ascertainment for total NRW was estimated to be 96.6% (95% CI: 96.1-97.1%) by a three-sources capture-recapture method applying a log-linear model [34]. Across census tracts, the completeness of ascertainment ranged between 92.6 and 100%.…”

Concordance of Commercial Data Sources for Neighborhood-Effects Studies

“…These methods are used to estimate a population size when a census may be infeasible or impossible to conduct. [19][20][21] Originally used for population estimation and for wildlife research and management, this technique has been applied to epidemiology for estimating incidence and prevalence of various diseases and health-related problems using data collected by two or more incomplete sources (e.g., hospital records and death certificates). [19][20][21][22] For the purposes of the present study, the capture-recapture method allowed estimation of the coverage (i.e., sensitivity or extent to which the databases included the complete number of listings) of two databases for ascertaining businesses.…”