Literature DB >> 29408188

A retrospective assessment of the completeness and timeliness of meningococcal disease notifications in the Republic of Ireland over a 16-year period, 1999-2015.

P O'Lorcain1, D E Bennett2, S L Morgan2, R J Cunney3, S M Cotter4, M T Cafferkey2, D M O'Flanagan4.   

Abstract

OBJECTIVES: To assess how invasive meningococcal disease (IMD) records held by the Irish Meningitis & Sepsis Reference Laboratory (IMSRL) compare to records of IMD notifications reported on the national integrated electronic Computerised Infectious Disease Reporting (CIDR) system. STUDY
DESIGN: We assessed the completeness, data quality and timeliness of IMD notifications and reference laboratory records for the period between 01 July 1999 and 30 June 2015 by identifying discrepant and/or missing data items in a matched case data set and by measuring the timeliness of case reporting.
METHODS: We matched anonymised cases notified to CIDR to records based at the IMSRL using birth, reporting and onset dates with gender and laboratory parameters of meningococcal strain characteristics and method of confirmation. Completeness, data quality and the timeliness of notifications were assessed by a stratified sensitivity-based technique and by calculating the average difference between IMSRL and CIDR reporting dates.
RESULTS: CIDR recorded a total of 3163 notifications, of which 2759 (87.2%) were matched to IMSRL records. Completeness of IMD case classification as confirmed was estimated to be >99%. Examining the levels of discrepant or missing data in both matched CIDR and IMSRL records as a measure of data quality, recording of demographic items and meningococcal group showed least differences, recording of laboratory case confirmation method and meningococcal strain characteristics were less well recorded, with detail on clinical presentation/diagnosis least well recorded. Overall average annual difference between CIDR and IMSRL recording dates was 3.2 days (95% confidence interval 2.6-3.8).
CONCLUSIONS: A high quality of IMD surveillance in Ireland was demonstrated, but scope for improvements in timeliness and capture of enhanced surveillance data regarding date of onset and strain-specific characteristics were identified.
Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Completeness; Ireland; Meningococcal disease; Timeliness

Mesh:

Year:  2018        PMID: 29408188     DOI: 10.1016/j.puhe.2017.11.027

Source DB:  PubMed          Journal:  Public Health        ISSN: 0033-3506            Impact factor:   2.427


  6 in total

1.  Estimation of the incidence of invasive meningococcal disease using a capture-recapture model based on two independent surveillance systems in Catalonia, Spain.

Authors:  Pilar Ciruela; Marta Vilaró; Gloria Carmona; Mireia Jané; Núria Soldevila; Tomás Garcia; Sergi Hernández; Laura Ruiz; Angela Domínguez
Journal:  BMJ Open       Date:  2022-06-21       Impact factor: 3.006

2.  Epidemiology of two decades of invasive meningococcal disease in the Republic of Ireland: an analysis of national surveillance data on laboratory-confirmed cases from 1996 to 2016.

Authors:  D Bennett; P O'Lorcain; S Morgan; S Cotter; M Cafferkey; R Cunney
Journal:  Epidemiol Infect       Date:  2019-01       Impact factor: 2.451

3.  Diversity of meningococci associated with invasive meningococcal disease in the Republic of Ireland over a 19 year period, 1996-2015.

Authors:  Désirée E Bennett; Kenneth L Meyler; Mary T Cafferkey; Robert J Cunney
Journal:  PLoS One       Date:  2020-02-13       Impact factor: 3.240

4.  Evaluation of the national surveillance system for invasive meningococcal disease, Italy, 2015-2018.

Authors:  Xanthi D Andrianou; Flavia Riccardo; Maria Grazia Caporali; Cecilia Fazio; Arianna Neri; Paola Vacca; Luigina Ambrosio; Patrizio Pezzotti; Paola Stefanelli
Journal:  PLoS One       Date:  2021-01-08       Impact factor: 3.240

5.  Risk factors for carriage of meningococcus in third-level students in Ireland: an unsupervised machine learning approach.

Authors:  Richard J Drew; Desirée Bennett; Sinéad O'Donnell; Robert Mulhall; Robert Cunney
Journal:  Hum Vaccin Immunother       Date:  2021-06-24       Impact factor: 4.526

6.  Evaluation of the surveillance system for invasive meningococcal disease (IMD) in the Netherlands, 2004-2016.

Authors:  Diederik A H Brandwagt; Arie van der Ende; Wilhelmina L M Ruijs; Hester E de Melker; Mirjam J Knol
Journal:  BMC Infect Dis       Date:  2019-10-17       Impact factor: 3.090

  6 in total

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