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Predictions by early indicators of the time and height of yearly influenza outbreaks in Sweden

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Author Info

  • Andersson, Eva

    ()
    (Statistical Research Unit, Department of Economics, School of Business, Economics and Law, Göteborg University)

  • Kühlmann-Berenzon, Sharon

    (Department of Epidemiology, Swedish Institute for Infectious Disease Control, Stockholm Group for Epidemic Modelling)

  • Linde, Annika

    (Department of Epidemiology, Swedish Institute for Infectious Disease Control)

  • Schiöler, Linus

    ()
    (Statistical Research Unit, Department of Economics, School of Business, Economics and Law, Göteborg University)

  • Rubinova, Sandra

    (Department of Epidemiology, Swedish Institute for Infectious Disease Control)

  • Frisén, Marianne

    ()
    (Statistical Research Unit, Department of Economics, School of Business, Economics and Law, Göteborg University)

Abstract

Aims: Methods for prediction of the peak of the influenza from early observations are suggested. These predictions can be used for planning purposes. Methods: In this study, new robust methods are described and applied on weekly Swedish data on influenza-like illness (ILI) and weekly laboratory diagnoses of influenza (LDI). Both simple and advanced rules for how to predict the time and height of the peak of LDI are suggested. The predictions are made using covariates calculated from data in early LDI reports. The simple rules are based on the observed LDI values while the advanced ones are based on smoothing by unimodal regression. The suggested predictors were evaluated by cross-validation and by application to the observed seasons. Results: The relation between ILI and LDI was investigated and it was found that the ILI variable is not a good proxy for the LDI variable. The advanced prediction rule regarding the time of the peak of LDI had a median error of 0.9 weeks, and the advanced prediction rule for the height of the peak had a median deviation of 28%. Conclusions: The statistical methods for predictions have practical usefulness.

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File URL: http://hdl.handle.net/2077/8475
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Bibliographic Info

Paper provided by Statistical Research Unit, Department of Economics, School of Business, Economics and Law, University of Gothenburg in its series Research Reports with number 2007:7.

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Length: 16 pages
Date of creation: 01 Jan 2007
Date of revision:
Publication status: Published in Scandinavian Journal of Public Health, 2008, pages 475-482.
Handle: RePEc:hhs:gunsru:2007_007

Contact details of provider:
Postal: Statistical Research Unit, University of Gothenburg, Box 640, SE 40530 GÖTEBORG
Web page: http://www.statistics.gu.se/

Related research

Keywords: Prediction; Influenza; Outbreak;

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