Prevalence of Artemisia Species Pollinosis in Western Poland: Impact of Climate Change on Aerobiological Trends, 1995-2004

Background: Artemisia species pollen represents a major cause of allergy in Central Europe. Variations in the pollen season, the influence of climate variables and the prevalence of pollinosis to it were analyzed in Poznan, in western Poland between 1995 and 2004. Methods: A Hirst volumetric spore trap was used for atmospheric sampling. Pollination date trend analysis and Spearman correlation tests were performed. Skin prick tests (SPT) and allergen specific immunoglobulin (Ig)E antibody measurements were performed in 676 and 524 patients, respectively. Results: The Artemisia species pollen season grew longer due to a clear advance in the starting day and only a slightly earlier end point; the peak day also came slightly earlier. Rainfall in the fi rst fortnight of July highly influenced pollen season severity. Temperature was directly correlated with daily Artemisia species pollen levels; relative humidity was inversely correlated. Twelve percent of patients had a positive SPT reaction to Artemisia species. Their symptoms were rhinitis and conjunctivitis (15%), atopic dermatitis (15%), chronic urticaria (14.3%), bronchial asthma (2.4%), and facial and disseminated dermatitis (1.3%). Elevated specifi c IgE concentrations were detected in the sera of 10.1% of patients. Conclusions: Artemisia species pollen is an important cause of pollinosis in western Poland. Pollen season intensity is highly influenced by rainfall in the previous weeks. Trends towards earlier season starts and longer duration, possibly caused by climate change, may have an impact on the allergic population.

Constructing a 7-day Ahead Forecast Model for Grass Pollen at North London, United Kingdom

A number of media outlets now issue medium-range (~7 day) weather forecasts on a regular basis. It is therefore logical that aerobiologists should attempt to produce medium-range forecasts for allergenic pollen that cover the same time period as the weather forecasts. The objective of this study is to construct a medium-range (< 7 day) forecast model for grass pollen at north London. The forecast models were produced using regression analysis based on grass pollen and meteorological data from 1990-1999 and tested on data from 2000 and 2002. The modelling process was improved by dividing the grass pollen season into three periods; the pre-peak, peak and post peak periods of grass pollen release. The forecast consisted of five regression models. Two simple linear regression models predicting the start and end date of the peak period, and three multiple regression models forecasting daily average grass pollen counts in the pre-peak, peak and post-peak periods. Overall the forecast models achieved 62% accuracy in 2000 and 47% in 2002, reflecting the fact that the 2002 grass pollen season was of a higher magnitude than any of the other seasons included in the analysis. This study has the potential to make a notable contribution to the field of aerobiology. Winter averages of the North Atlantic Oscillation were used to predict certain characteristics of the grass pollen season, which presents an important advance in aerobiological work. The ability to predict allergenic pollen counts for a period between five and seven days will benefit allergy sufferers. Furthermore, medium-range forecasts for allergenic pollen will be of assistance to the medical profession, including allergists planning treatment and physicians scheduling clinical trials.