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Predictive performance of telenursing complaints in influenza surveillance: a prospective cohort study in Sweden
Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
Department of Computer and Information Science, Linköping University, Linköping, Sweden.
Linnaeus Centre HEAD, Department of Behavioural Sciences, Linköping University, Linköping, Sweden.
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2014 (English)In: Eurosurveillance, ISSN 1025-496X, E-ISSN 1560-7917, Vol. 19, no 46, 20966- p.Article in journal (Refereed) Published
Abstract [en]

Syndromic data sources have been sought to improve the timely detection of increased influenza transmission. This study set out to examine the prospective performance of telenursing chief complaints in predicting influenza activity. Data from two influenza seasons (2007/08 and 2008/09) were collected in a Swedish county (population 427,000) to retrospectively determine which grouping of telenursing chief complaints had the largest correlation with influenza case rates. This grouping was prospectively evaluated in the three subsequent seasons. The best performing telenursing complaint grouping in the retrospective algorithm calibration was fever (child, adult) and syncope (r=0.66; p<0.001). In the prospective evaluation, the performance of 14-day predictions was acceptable for the part of the evaluation period including the 2009 influenza pandemic (area under the curve (AUC)=0.84; positive predictive value (PPV)=0.58), while it was strong (AUC=0.89; PPV=0.93) for the remaining evaluation period including only influenza winter seasons. We recommend the use of telenursing complaints for predicting winter influenza seasons. The method requires adjustments when used during pandemics.

Place, publisher, year, edition, pages
2014. Vol. 19, no 46, 20966- p.
National Category
Public Health, Global Health, Social Medicine and Epidemiology
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URN: urn:nbn:se:umu:diva-98435ISI: 000345424100004PubMedID: 25425514Scopus ID: 2-s2.0-84911867982OAI: oai:DiVA.org:umu-98435DiVA: diva2:785910
Available from: 2015-02-04 Created: 2015-01-22 Last updated: 2017-12-05Bibliographically approved

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Strömgren, MagnusHolm, Einar

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