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

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General discussion<br />

and hence positive predictive value, will often already considerably improve the<br />

knowledge of the number of patients and <strong>in</strong>fectious disease <strong>in</strong>cidence rates, as well as the<br />

completeness of <strong>in</strong>formation on specific demographic, diagnostic or epidemiological<br />

variables. An example of an <strong>in</strong>fectious disease surveillance system that rout<strong>in</strong>ely l<strong>in</strong>ks<br />

notification data with laboratory data is the ETS <strong>in</strong> England and Wales. This type of<br />

record-l<strong>in</strong>kage should ideally be web-based for a timely reflection of trends. An example<br />

of a web-based notification system is OSIRIS <strong>in</strong> the Netherlands but this system is not<br />

l<strong>in</strong>ked to laboratory reports. 13 For improv<strong>in</strong>g quality, completeness and timel<strong>in</strong>ess of<br />

<strong>in</strong>fectious disease surveillance, a web-based <strong>in</strong>fectious disease surveillance system that<br />

rout<strong>in</strong>ely l<strong>in</strong>ks notification data with laboratory data could essentially fulfil the qualities<br />

once attributed to capture-<strong>recapture</strong> analysis.<br />

11.3 Conclusions and recommendations<br />

Conclusions<br />

• Infectious disease <strong>in</strong>cidence capture-<strong>recapture</strong> analysis requires adequate knowledge<br />

of disease, patients and registrations.<br />

• In capture-<strong>recapture</strong> analysis small variations <strong>in</strong> the quality of data and record-l<strong>in</strong>kage<br />

can lead to highly variable outcomes. Therefore previous successful <strong>in</strong>fectious disease<br />

capture-<strong>recapture</strong> studies cannot be repeated uncritically.<br />

• Hospital episode statistics often conta<strong>in</strong> many false-positive records, which, when not<br />

identified, lead to biased capture-<strong>recapture</strong> estimates.<br />

• When categorical covariates associated with the probability of capture <strong>in</strong> an <strong>in</strong>fectious<br />

disease register are present, covariate capture-<strong>recapture</strong> analysis can reduce bias as a<br />

result of heterogeneity.<br />

• In the absence of a gold standard, truncated models can be used as a heuristic tool to<br />

identify possible failure <strong>in</strong> log-l<strong>in</strong>ear models, especially when saturated models are<br />

selected.<br />

Recommendations<br />

• Infectious diseases capture-<strong>recapture</strong> studies should be performed with a multidiscipl<strong>in</strong>ary<br />

team <strong>in</strong>clud<strong>in</strong>g public health physicians, cl<strong>in</strong>icians, statisticians and data<br />

managers.<br />

• For more reliable record-l<strong>in</strong>kage of notifiable <strong>in</strong>fectious disease registers the Dutch<br />

Infectious Disease Act 1999 should be amended and provide record<strong>in</strong>g the date of<br />

birth of the patients <strong>in</strong>stead of the year of birth.<br />

171

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