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dc.contributor.authorGreeff, Sabine C de
dc.contributor.authorSpanjaard, Lodewijk
dc.contributor.authorDankert, Jacob
dc.contributor.authorHoebe, Christian J P A
dc.contributor.authorNagelkerke, Nico J D
dc.contributor.authorMelker, Hester E de
dc.date.accessioned2006-10-06T08:43:19Z
dc.date.available2006-10-06T08:43:19Z
dc.date.issued2006-05-10
dc.identifier.citationEur. J. Epidemiol. 2006, 21(4):315-21en
dc.identifier.issn0393-2990
dc.identifier.pmid16685583
dc.identifier.doi10.1007/s10654-006-0020-z
dc.identifier.urihttp://hdl.handle.net/10029/4908
dc.description.abstractIn order to come to a reliable evaluation of the effectiveness of the chosen vaccination policy regarding meningococcal disease, the completeness of registrations on meningococcal disease in the Netherlands was estimated with the capture-recapture method. Data over 1993-1998 were collected from (A) mandatory notifications (n = 2926); (B) hospital registration (n = 3968); (C) laboratory surveillance (n = 3484). As the standard capture-recapture method does not take into account false positive diagnoses, we developed a model to adjust for the lack of specificity of our sources. We estimated that 1363 cases were not registered in any of the three sources in the period of study. The completeness of the three sources was therefore estimated at 49% for source A, 67% for source B and 58% for source C. After adjustment for false positive diagnoses, the completeness of source A, B, and C was estimated as 52%, 70% and 62%, respectively. The capture-recapture methods offer an attractive approach to estimate the completeness of surveillance sources and hence contribute to a more accurate estimate of the disease burden under study. However, the method does not account for higher-order interactions or presence of false positive diagnoses. Being aware of these limitations, the capture-recapture method still elucidates the (in)completeness of sources and gives a rough estimate of this (in)completeness. This makes a more accurate monitoring of disease incidence possible and hence attributes to a more reliable foundation for the design and evaluation of health interventions such as vaccination programs.
dc.format.extent195254 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.titleUnderreporting of meningococcal disease incidence in the Netherlands: results from a capture-recapture analysis based on three registration sources with correction for false positive diagnoses.en
dc.typeArticleen
dc.format.digYES
refterms.dateFOA2018-12-18T13:40:00Z
html.description.abstractIn order to come to a reliable evaluation of the effectiveness of the chosen vaccination policy regarding meningococcal disease, the completeness of registrations on meningococcal disease in the Netherlands was estimated with the capture-recapture method. Data over 1993-1998 were collected from (A) mandatory notifications (n = 2926); (B) hospital registration (n = 3968); (C) laboratory surveillance (n = 3484). As the standard capture-recapture method does not take into account false positive diagnoses, we developed a model to adjust for the lack of specificity of our sources. We estimated that 1363 cases were not registered in any of the three sources in the period of study. The completeness of the three sources was therefore estimated at 49% for source A, 67% for source B and 58% for source C. After adjustment for false positive diagnoses, the completeness of source A, B, and C was estimated as 52%, 70% and 62%, respectively. The capture-recapture methods offer an attractive approach to estimate the completeness of surveillance sources and hence contribute to a more accurate estimate of the disease burden under study. However, the method does not account for higher-order interactions or presence of false positive diagnoses. Being aware of these limitations, the capture-recapture method still elucidates the (in)completeness of sources and gives a rough estimate of this (in)completeness. This makes a more accurate monitoring of disease incidence possible and hence attributes to a more reliable foundation for the design and evaluation of health interventions such as vaccination programs.


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