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International Journal of Biometeorology

, Volume 58, Issue 6, pp 1047–1055 | Cite as

Development and validation of a 5-day-ahead hay fever forecast for patients with grass-pollen-induced allergic rhinitis

  • Letty A. de WegerEmail author
  • Thijs Beerthuizen
  • Pieter S. Hiemstra
  • Jacob K. Sont
Original Paper

Abstract

One-third of the Dutch population suffers from allergic rhinitis, including hay fever. In this study, a 5-day-ahead hay fever forecast was developed and validated for grass pollen allergic patients in the Netherlands. Using multiple regression analysis, a two-step pollen and hay fever symptom prediction model was developed using actual and forecasted weather parameters, grass pollen data and patient symptom diaries. Therefore, 80 patients with a grass pollen allergy rated the severity of their hay fever symptoms during the grass pollen season in 2007 and 2008. First, a grass pollen forecast model was developed using the following predictors: (1) daily means of grass pollen counts of the previous 10 years; (2) grass pollen counts of the previous 2-week period of the current year; and (3) maximum, minimum and mean temperature (R 2 = 0.76). The second modeling step concerned the forecasting of hay fever symptom severity and included the following predictors: (1) forecasted grass pollen counts; (2) day number of the year; (3) moving average of the grass pollen counts of the previous 2 week-periods; and (4) maximum and mean temperatures (R 2 = 0.81). Since the daily hay fever forecast is reported in three categories (low-, medium- and high symptom risk), we assessed the agreement between the observed and the 1- to 5-day-ahead predicted risk categories by kappa, which ranged from 65 % to 77 %. These results indicate that a model based on forecasted temperature and grass pollen counts performs well in predicting symptoms of hay fever up to 5 days ahead.

Keywords

Hay fever forecast Grass pollen forecast Grass pollen Allergic rhinitis Multiple regression analysis 

Notes

Acknowledgments

This study was supported by the Netherlands Asthma Foundation (grant: 3.4.06.074). We thank Dr. Robert Mureau from the Royal Netherlands Meteorological Institute for supplying the forecasted weather parameters.

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Copyright information

© ISB 2013

Authors and Affiliations

  • Letty A. de Weger
    • 1
    Email author
  • Thijs Beerthuizen
    • 2
  • Pieter S. Hiemstra
    • 1
  • Jacob K. Sont
    • 2
  1. 1.Department of PulmonologyLeiden University Medical CenterLeidenThe Netherlands
  2. 2.Department of Medical Decision MakingLeiden University Medical CenterLeidenThe Netherlands

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