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Revista Española de Salud Pública

On-line version ISSN 2173-9110Print version ISSN 1135-5727

Abstract

IZQUIERDO CARRENO, Ana; MATUTE CRUZ, Petra  and  MARTINEZ NAVARRO, Ferrán. The Use of the Capture-Recapture Method in Evaluating the Epidemiological Meningococcal Disease Monitoring System in Tenerife, Spain (1999-2000). Rev. Esp. Salud Publica [online]. 2003, vol.77, n.6, pp.701-711. ISSN 2173-9110.

Background: Meningococcal Disease is mainly monitored passively on the Canary Islands, the regular Compulsory Disease Notification channels being used. The objective of this study includes describing the qualitative and quantitative aspects of this system and evaluating the exhaustiveness, by means of the capture-recapture system, of three information sources. Methods: This study covers the 1999-2001 period in Tenerife. The information was gathered from three sources: the Compulsory Disease Notification System, the Microbiology Laboratories and the hospital Minimum Basic Data Set. The Evaluation Protocols of the Monitoring System of the Atlanta Centers of Disease Control and Prevention were used. A log-linear model was used for estimating the number of cases. The calculations of the exhaustiveness and the 95% confidence intervals were done in the SPSS10 statistics package. Results: The system was found to have an 84.9% sensitivity, and an 80.4% positive predictive value. The delay in notification (timeliness) fell within the 0.5 - 13-day range, averaging 3 days. The system was found to have a 76.6% overall acceptability. The exhaustiveness value was 98.1%. Conclusions: This disease is being monitored well, with a degree of sensitivity which would be revealing of a good notification level, also confirmed by its exhaustiveness. Although the positive predictive value is high, this could be indicative of the expeditious starting of antibiotic treatment which would hinder microbiological confirmation. The system is timely, affording the possibility of measures being taken for fast intervention.

Keywords : Communicable diseases; Neisseria meningitidis; Health surveillance; Information systems.

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