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First published June 28, 2007 as JAMIA PrePrint; doi:10.1197/jamia.M2328
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J Am Med Inform Assoc. 2007;14:626-631. DOI 10.1197/jamia.M2328.
© 2007 American Medical Informatics Association


Research Paper

Timeliness of Data Sources Used for Influenza Surveillance

Lynne Dailey, MPH*, Rochelle E. Watkins, PhD and Aileen J. Plant, MBBS, DTM&H, MPH, PhD

Australian Biosecurity CRC for Emerging Infectious Disease, Division of Health Sciences, Curtin University of Technology, Perth, Western Australia.

* Correspondence and reprints: Lynne Dailey, Australian Biosecurity CRC, Health Research Campus, Curtin University of Technology, GPO Box U1987 Perth, Western Australia 6845 (Email: lynne.dailey{at}postgrad.curtin.edu.au).

Received for publication: 11/13/06; accepted for publication: 05/20/07.

Objective: In recent years, influenza surveillance data has expanded to include alternative sources such as emergency department data, absenteeism reports, pharmaceutical sales, website access and health advice calls. This study presents a review of alternative data sources for influenza surveillance, summarizes the time advantage or timeliness of each source relative to traditional reporting and discusses the strengths and weaknesses of competing approaches.

Methods: A literature search was conducted on Medline to identify relevant articles published after 1990. A total of 15 articles were obtained that reported the timeliness of an influenza surveillance system. Timeliness was described by peak comparison, aberration detection comparison and correlation.

Results: Overall, the data sources were highly correlated with traditional sources and had variable timeliness. Over-the-counter pharmaceutical sales, emergency visits, absenteeism and health calls appear to be more timely than physician diagnoses, sentinel influenza-like-illness surveillance and virological confirmation.

Conclusions: The methods used to describe timeliness vary greatly between studies and hence no strong conclusions regarding the most timely source/s of data can be reached. Future studies should apply the aberration detection method to determine data source timeliness in preference to the peak comparison method and correlation.







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Copyright © 2007 by the American Medical Informatics Association.