Rob van Hest Capture-recapture Methods in Surveillance - RePub ...

General discussion
the screening programme. Often cross-validation of the population estimates from
truncated models is not possible. However, we could compare our estimates with an
independent assessment of the number of problematic illicit drug users in Rotterdam in
2003 established through two-source capture-recapture analysis that used a similar casedefinition
of the target group. These capture-recapture estimates were comparable to
those of the truncated models. In the context of its advantages and limitations, we
conclude that the use of truncated population estimation models is a feasible and valid
method for estimating the coverage of a public health intervention programme among
hidden populations.
A more detailed study of the validity of truncated population estimation models
in infectious disease surveillance compared the performance of some truncated
population estimation models with three-source log-linear capture-recapture analysis
using data from published and current capture-recapture studies on infectious disease
incidence (chapter 10). This comparative research was triggered by the results of the
studies described in chapter 6 and chapter 8, indicating that conventional three-source
log-linear capture-recapture models sometimes break down and produce unexpected and
implausible results. Solely relying on three-source capture-recapture analysis seemed
inappropriate and we perceived that a tool is needed to cross-validate capture-recapture
estimates for infectious disease incidence. Ideally, this would be a model robust to
violation of all capture-recapture assumptions but such models do not exist. We used
truncated models because they performed well when compared to log-linear capturerecapture
analysis earlier. 30 The comparative research was feasible as truncated models are
easy to apply and can be used on the data of three-source capture-recapture studies (but
not vice-versa). A limitation of our approach is that the number of possible frequency
classes is restricted to three, violating the “infinite number of sources” assumption for
truncated Poisson models. The truncated models are at least as vulnerable to violation of
the perfect positive predictive value, perfect record-linkage, closed population and
independent registers assumptions as capture-recapture models. It has been argued that
truncated models are more robust to heterogeneity among the patients than capturerecapture
studies. 25,31 In contrast, the equiprobability assumption of the truncated models
is almost certainly violated when using multiple-source data from capture-recapture
studies. Therefore we introduced the coefficient of variation, a measure of variability in
the coverages of the three data sources for capture-recapture studies, to estimate the error
from the data. We conclude that, in the context of validity, for estimating infectious
disease incidence and completeness of notification independent and parsimonious threesource
log-linear capture-recapture models are preferable compared to the truncated
models examined. When saturated models are selected as best-fitting model and the
estimates are unexpectedly high and seem implausible, the data should be re-examined
with truncated models as a heuristic tool, in the absence of a gold standard. Possible
failure in the saturated log-linear model or unidentified violation of the underlying
assumptions should be suspected when the truncated models produce a (considerably)
lower estimated number of infectious disease patients.
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