Capture–recapture analysis has been used to evaluate infectious disease surveillance. Violation of the underlying assumptions can jeopardize the validity of the capture–recapture estimates and a tool is needed for cross-validation. We re-examined 19 datasets of log-linear model capture–recapture studies on infectious disease incidence using three truncated models for incomplete count data as alternative population estimators. The truncated models yield comparable estimates to independent log-linear capture–recapture models and to parsimonious log-linear models when the number of patients is limited, or the ratio between patients registered once and twice is between 0·5 and 1·5. Compared to saturated log-linear models the truncated models produce considerably lower and often more plausible estimates. We conclude that for estimating infectious disease incidence independent and parsimonious three-source log-linear capture–recapture models are preferable but truncated models can be used as a heuristic tool to identify possible failure in log-linear models, especially when saturated log-linear models are selected.,
Epidemiology and Infection
Erasmus MC: University Medical Center Rotterdam

van Hest, N. A. H., Grant, A. D., Smit, F., Story, A., & Richardus, J. H. (2008). Estimating infectious diseases incidence: validity of capture–recapture analysis and truncated models for incomplete count data. Epidemiology and Infection, 136(1), 14–22. doi:10.1017/S0950268807008254