Recommendations for presentation and evaluation of capture-recapture estimates in epidemiology.
We propose 15 recommendations for approaches to capture-recapture analysis in epidemiology. We apply them to a report of such an analysis of a measles epidemic [McGilchrist et al., J Clinical Epidemiol 1996, 49: 293-296] and to comments thereon by R. C. Cormack [J Clinical Epidemiol 1999; 52: 909-914]. The latter challenged the utility of the data on the measles outbreak for any reliable capture-recapture estimates. We suggest that, adopting the perspective of W. Edwards Deming, one can only make judgments as to the reliability of capture-recapture data, methods, and derived estimates in the light of (i.e., conditional upon) their eventual intended use. Capture-recapture approaches "unreliable" from one perspective may be "reliable," and/or more appropriately, "useful" from another. We consider the utility of ancillary and ad hoc information that may be available or worth seeking to supplement a capture-recapture analysis. We use information within the study of McGilchrist et al. to illustrate how, with such ancillary information, one may overcome the main thrust of the objections of Cormack in situations in which one observes apparently anomalous or hard to understand data structures. Making certain simple assumptions we regard as plausible, we estimate the number of affected in the measles epidemic as between about 700-1300. We derive this from data on 502 cases in a Register, an ad hoc sample of 91 cases in one age group in the general population, and the report of 41 cases in both of these. Our result is only 15-30% the total implied by the estimates McGilchrist et al. derived with more complex methods and many assumptions in addition to our own. We discuss various approaches to evaluating "reliability" of our estimate conditional upon intended uses by policy makers.
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School of Public Health, University of California, Berkeley 94720-7360, USA. ebhook@socrates.berkeley.edu
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D001315:Australia / Q000453:epidemiology; D002648:Child; D002675:Child, Preschool; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D004812:Epidemiologic Methods; D006801:Humans; D007223:Infant; D016014:Linear Models; D008457:Measles / Q000453:epidemiology*; D011159:Population Surveillance