Factors that determine the severity of <Emphasis Type="Italic">Betula</Emphasis> spp. pollen seasons in Poland (Poznań and Krakow) and the United Kingdom (Worcester and London)

The aim of this paper is to analyse variations in the severity of Betula pollen seasons, particularly in relation to meteorological parameters at four sites, Poznań and Krakow in Poland, and Worcester and London in the United Kingdom. Results show that there is a significant relationship between Betula pollen season severity and weather conditions both in the year before pollination and in the same year that pollen is released from the plant. Furthermore, it is likely that the magnitude of birch pollen seasons in Poznań, Worcester and London is linked in some way to different phases of the North Atlantic Oscillation (NAO). Significant positive relationships exist between birch pollen counts at Poznań and temperatures, rainfall and averages of the NAO in the year before pollination. An opposite relationship is evident at the two sites studied in the United Kingdom. There were significant positive correlations between the severity of birch pollen seasons recorded at Worcester and temperatures and averages of the NAO during the winter and spring in the year of pollination, and negative correlations at both Worcester and London with similar variables from the previous year. In addition, Betula pollen seasons in Krakow do not appear to be influenced by the NAO, which is probably the result of Krakow having a more continental climate.     

Statistical modeling,forecasting and time series analysis of birch phenology in Montreal,Canada

The aim of this study was to analyse birch pollen time series observed in Montreal (Canada) in order to understand the link between inter-annual variability of phenology and environmental factors and to build predictive models for the upcoming pollen season. Modeling phenology is challenging, especially in Canada, where phenological observations are rare. Nevertheless, understanding phenology is required for scientific applications (e.g. inputs to numerical models of pollen dispersion) but also to help allergy sufferers to better prepare their medication and avoidance strategies before the start of the pollen season. We used multivariate statistical regression to analyse and predict phenology. The predictors were drawn from a large basin (over 60) of potential environmental predictors including meteorological data and global climatic indices such NAO (North Atlantic Oscillation index) and ENSO/MEI (Multivariate Enso Index). Results of this paper are summarized as follows: (1) an accurate forecast for the upcoming season starting date of the birch pollen season was obtained (showing low bias and total forecast error of about 4 days in Montreal), (2) NAO and ENSO/MEI indices were found to be well correlated (i.e. 44% of the variance explained) with birch phenology, (3) a long-term trend of 2.6 days per decade (p < 0.1) towards longer season duration was found for the length of the birch pollen season in Montreal. Finally, perturbations of the quasi-biennial cycle of birch were observed in the pollen data during the pollen season following the Great Ice Storm of 1998 which affected south-eastern Canada.     

The effects of large-scale atmospheric fields on the cypress pollen season in Tuscany (Central Italy)

This research was performed for the purpose of analysing the relationships between large-scale meteorological information, in particular the North Atlantic Oscillation (NAO) index and the Sea Surface Temperature (SST), and the timing and magnitude of the Cupressaceae pollen season in the Pistoia district of Central Italy. The results demonstrated that in specific periods of the year, the NAO index, by partially determining the distribution of the main meteorological variables over the study area, is negatively correlated with the start and the end, as well as the peak day of pollen concentration. Pollen data were also correlated with the SST of the North Atlantic Ocean east of the Azores for the September–December period of the previous year, which is significant for exploring possibilities in terms of predicting the timing and magnitude of the cypress pollen season. The analysis of such meteorological variables and indices could be used to improve the existing forecasting systems of the phenology of the cypress pollen season. Moreover, the possibility of using meteorological information freely available on internet could cut costs and reduce spatial and temporal representativeness limitations relating to weather monitoring in loco.     

Regional and seasonal variation in airborne grass pollen levels between cities of Australia and New Zealand

Although grass pollen is widely regarded as the major outdoor aeroallergen source in Australia and New Zealand (NZ), no assemblage of airborne pollen data for the region has been previously compiled. Grass pollen count data collected at 14 urban sites in Australia and NZ over periods ranging from 1 to 17 years were acquired, assembled and compared, revealing considerable spatiotemporal variability. Although direct comparison between these data is problematic due to methodological differences between monitoring sites, the following patterns are apparent. Grass pollen seasons tended to have more than one peak from tropics to latitudes of 37°S and single peaks at sites south of this latitude. A longer grass pollen season was therefore found at sites below 37°S, driven by later seasonal end dates for grass growth and flowering. Daily pollen counts increased with latitude; subtropical regions had seasons of both high intensity and long duration. At higher latitude sites, the single springtime grass pollen peak is potentially due to a cooler growing season and a predominance of pollen from C₃ grasses. The multiple peaks at lower latitude sites may be due to a warmer season and the predominance of pollen from C₄ grasses. Prevalence and duration of seasonal allergies may reflect the differing pollen seasons across Australia and NZ. It must be emphasized that these findings are tentative due to limitations in the available data, reinforcing the need to implement standardized pollen-monitoring methods across Australasia. Furthermore, spatiotemporal differences in grass pollen counts indicate that local, current, standardized pollen monitoring would assist with the management of pollen allergen exposure for patients at risk of allergic rhinitis and asthma.     

Poaceae pollen in the air depending on the thermal conditions

The relationship between the meteorological elements, especially the thermal conditions and the Poaceae pollen appearance in the air, were analysed as a basis to construct a useful model predicting the grass season start. Poaceae pollen concentrations were monitored in 1991–2012 in Kraków using the volumetric method. Cumulative temperature and effective cumulative temperature significantly influenced the season start in this period. The strongest correlation was seen as the sum of mean daily temperature amplitudes from April 1 to April 14, with mean daily temperature >15 °C and effective cumulative temperature >3 °C during that period. The proposed model, based on multiple regression, explained 57 % of variation of the Poaceae season starts in 1991–2010. When cumulative mean daily temperature increased by 10 °C, the season start was accelerated by 1 day. The input of the interaction between these two independent variables into the factor regression model caused the increase in goodness of model fitting. In 2011 the season started 5 days earlier in comparison with the predicted value, while in 2012 the season start was observed 2 days later compared to the predicted day. Depending on the value of mean daily temperature from March 18th to the 31st and the sum of mean daily temperature amplitudes from April 1st to the 14th, the grass pollen seasons were divided into five groups referring to the time of season start occurrence, whereby the early and moderate season starts were the most frequent in the studied period and they were especially related to mean daily temperature in the second half of March.     

Variations in Quercus sp. pollen seasons (1996–2011) in Poznań, Poland,in relation to meteorological parameters

The aim of this study is to supply detailed information about oak (Quercus sp.) pollen seasons in Poznań, Poland, based on a 16-year aerobiological data series (1996–2011). The pollen data were collected using a volumetric spore trap of the Hirst design located in Poznań city center. The limits of the pollen seasons were calculated using the 95 % method. The influence of meteorological parameters on temporal variations in airborne pollen was examined using correlation analysis. Start and end dates of oak pollen seasons in Poznań varied markedly from year-to-year (14 and 17 days, respectively). Most of the pollen grains (around 75 % of the seasonal pollen index) were recorded within the first 2 weeks of the pollen season. The tenfold variation was observed between the least and the most intensive pollen seasons. These fluctuations were significantly related to the variation in the sum of rain during the period second fortnight of March to first fortnight of April the year before pollination (r = 0.799; p < 0.001). During the analyzing period, a significant advance in oak pollen season start dates was observed (?0.55 day/year; p = 0.021), which was linked with an increase in the mean temperature during the second half of March and first half of April (+0.2 °C; p = 0.014). Daily average oak pollen counts correlated positively with mean and maximum daily temperatures, and negatively with daily rainfall and daily mean relative humidity.     

Spatial variations in the dynamics of the Alnus and Corylus pollen seasons in Poland

The objective of this study was to analyse the dynamics of the Alnus and Corylus pollen seasons in Poland with reference to spatial and seasonal differentiation. Aerobiological monitoring was performed in 10 cities, in 1994–2007. Five characteristics defining the pollen season were considered: 1. beginning and end dates of the season phases (5, 25, 50, 75, 95% of annual totals), 2. pollen season duration (90% method), 3. skewness and 4. kurtosis of airborne pollen curves, and 5. annual pollen totals. The beginning of the Corylus pollen season in Warsaw started on the 53rd day of a year. The Alnus pollen season started 9.5 days (SE = 1.4) later. The start of the season for both taxa was delayed by 3.3 (SE = 0.5) days for each 100 km towards the east. The Corylus pollen season lasted about 15 days longer than the Alnus season. Season duration for both taxa decreased towards the east by 3.5 days (SE = 0.7) and towards the north by 1.3 days (SE = 0.6) for each 100 km. Seasonal dynamics of both taxa are skewed to the right. In cities located west of Warsaw the dynamics are more skewed (except at Szczecin, Wroclaw). Asymmetry decreases towards the east by 0.16/100 km. Almost all kurtosis values of pollen-season dynamics were positive and higher for Alnus. Kurtosis values for both taxa increase together with delay of the pollen season beginning by 4% per day (p < 0.0001). Mean pollen total increases: for Corylus mainly towards the north (by 64%/100 km), for Alnus mainly towards the west (by 15%/100 km). Geographical location (longitude and latitude) determines: the start and duration of the pollen season, skewness of the pollen curve, and annual totals.     

Climate change effect on Betula (birch) and Quercus (oak) pollen seasons in the United States

Climatic change is expected to affect the spatiotemporal patterns of airborne allergenic pollen, which has been found to act synergistically with common air pollutants, such as ozone, to cause allergic airway disease (AAD). Observed airborne pollen data from six stations from 1994 to 2011 at Fargo (North Dakota), College Station (Texas), Omaha (Nebraska), Pleasanton (California), Cherry Hill and Newark (New Jersey) in the US were studied to examine climate change effects on trends of annual mean and peak value of daily concentrations, annual production, season start, and season length of Betula (birch) and Quercus (oak) pollen. The growing degree hour (GDH) model was used to establish a relationship between start/end dates and differential temperature sums using observed hourly temperatures from surrounding meteorology stations. Optimum GDH models were then combined with meteorological information from the Weather Research and Forecasting (WRF) model, and land use land coverage data from the Biogenic Emissions Land use Database, version 3.1 (BELD3.1), to simulate start dates and season lengths of birch and oak pollen for both past and future years across the contiguous US (CONUS). For most of the studied stations, comparison of mean pollen indices between the periods of 1994–2000 and 2001–2011 showed that birch and oak trees were observed to flower 1–2 weeks earlier; annual mean and peak value of daily pollen concentrations tended to increase by 13.6 %–248 %. The observed pollen season lengths varied for birch and for oak across the different monitoring stations. Optimum initial date, base temperature, and threshold GDH for start date was found to be 1 March, 8 °C, and 1,879 h, respectively, for birch; 1 March, 5 °C, and 4,760 h, respectively, for oak. Simulation results indicated that responses of birch and oak pollen seasons to climate change are expected to vary for different regions.     

Predicting tree pollen season start dates using thermal conditions

Thermal conditions at the beginning of the year determine the timing of pollen seasons of early flowering trees. The aims of this study were to quantify the relationship between the tree pollen season start dates and the thermal conditions just before the beginning of the season and to construct models predicting the start of the pollen season in a given year. The study was performed in Krakow (Southern Poland); the pollen data of Alnus, Corylus and Betula were obtained in 1991–2012 using a volumetric method. The relationship between the tree pollen season start, calculated by the cumulated pollen grain sum method, and a 5-day running means of maximum (for Alnus and Corylus) and mean (for Betula) daily temperature was found and used in the logistic regression models. The estimation of model parameters indicated their statistically significance for all studied taxa; the odds ratio was higher in models for Betula, comparing to Alnus and Corylus. The proposed model makes the accuracy of prediction in 83.58 % of cases for Alnus, in 84.29 % of cases for Corylus and in 90.41 % of cases for Betula. In years of model verification (2011 and 2012), the season start of Alnus and Corylus was predicted more precisely in 2011, while in case of Betula, the model predictions achieved 100 % of accuracy in both years. The correctness of prediction indicated that the data used for the model arrangement fitted the models well and stressed the high efficacy of model prediction estimated using the pollen data in 1991–2010.     

Trends in atmospheric concentrations of weed pollen in the context of recent climate warming in Poznań (Western Poland)

A significant increase in summer temperatures has been observed for the period 1996–2011 in Poznań, Poland. The phenological response of four weed taxa, widely represented by anemophilous species (Artemisia spp., Rumex spp. and Poaceae and Urticaceae species) to this recent climate warming has been analysed in Poznań by examining the variations in the course of airborne pollen seasons. Pollen data were collected by 7-day Hirst-type volumetric trap. Trends in pollen seasons were determined using Mann–Kendall test and Sen’s slope estimator, whereas the relationships between meteorological and aerobiological data were established by Spearman’s rank correlation coefficient. Significant trends in pollen data were detected. The duration of pollen seasons of all analysed taxa increased (from +2.0 days/year for Urticaceae to +3.8 days/year for Rumex), which can be attributed to a delay in pollen season end dates rather than earlier start dates. In addition, the intensity of Artemisia pollen seasons significantly decreased and correlates with mean July–September daily minimum temperatures (r?=??0.644, p?Rumex pollen seasons. The results of this study show that observed shifts in weed pollen seasons in Poznań, i.e. longer duration and later end dates, might be caused by the recorded increase in summer temperature. This influence was the strongest in relation to Artemisia, which is the taxon that flowers latest in the year. The general lack of significant correlations between Rumex and Urticaceae pollen seasons and spring and/or summer temperature suggests that other factors, e.g. land use practices, could also be partially responsible for the observed shifts in pollen seasons.     

Differences in atmospheric trees pollen seasons in winter, spring and summer in two European geographic areas, Spain and Italy

The global climate change reported over recent years may prompt changes in the atmospheric pollen season (APS). The aim of this study is to evaluate the possible impact provoked by meteorological conditions variations at different seasons of the year or different geographical areas on APS. Alnus, Betula and Castanea atmospheric pollen seasons and trends during the last 17 years at Ourense and Vigo (Galicia—NW Spain) and Perugia (Italy) were analysed. Possible incidence of the meteorological trends observed in the different cities on the atmospheric pollen seasons and the chill and heat requirements were evaluated. Pollen data from Ourense, Vigo and Perugia (1995–2011) were used. Pollen sampling was performed using LANZONI VPPS 2000 volumetric traps (Hirst in Ann Appl Biol 36:257–265, 1952), placed on top of different buildings at a similar height from the ground. Several methods, dates and threshold temperatures for determining the chill and heat requirements needed to trigger flowering were tested. Different temporary order in the pollination sequence was observed between the three pollen types studied in the three sites. Alnus flowers few days in advance in Ourense respecting to Vigo and 1 month earlier than Perugia. The Betula flowering start date in Ourense and Vigo is almost simultaneous, taking place only 5 days in advance with respect to Perugia. Finally, scarce differences in the APS onset of Castanea were detected between the three cities. The variations observed among the two areas (Umbria, Italy and Galicia, Spain) in the onset of pollen season in the winter or spring flowering trees could be explained by differences in the thermal requirements needed for flowering as consequence of the climatic conditions recorded during the previous period to flowering. The length of the chilling and heat period as well as the thermal requirements obtained showed differences between geographical areas. The chill requirements accumulated were higher in Perugia than Ourense and Vigo. By contrary, the lowest heat accumulation was achieved in Perugia. The observed trends in the APS characteristics and the weather-related parameters were not homogeneous both in the pollen types and sites. The pollen index of Betula and Castanea pollen in Ourense shows a significant trend to increase.     

A comparative study of airborne pollen concentrations of three allergenic types

Airborne concentrations of pollen from Betula (birch), Poaceae (grasses) and Artemisia (mugwort) are compared during a seven year period (90–96) with respect to both quantitative and seasonal aspects, at three different sampling sites, one in Estonia (Tartu) and two in Sweden (Stockholm and Roma on the island of Gotland). All three taxa occur in the region and are well‐known causes of allergic sensitisation. The annual total and peak values of birch, grass and mugwort pollen were found to be much higher in Tartu than in Stockholm and Roma. Both the birch and the grass pollen seasons ended later in Stockholm than in Roma and Tartu. The mugwort flowering season always began earlier in Stockholm than at the other sites, and more days elapsed between start day and peak day in Stockholm than in Tartu.     

Types of Artemisia pollen season depending on the weather conditions in Wrocław (Poland), 2002–2011

The aim of the study was to characterise Artemisia pollen season types according to weather conditions in Wroc?aw (south-western Poland) in the years 2002–2011. Over the period analysed, the start date of the pollen season (determined by the 95 % method) ranged from 10 July 2002 to 28 July 2010. The start date of the pollen season can be determined by using Crop Heat Units (CHUs). During the period 2002–2011, the Artemisia pollen season started after the cumulative value of CHUs had reached 2,000–2,100 °C. The three distinguished types of Artemisia pollen season are best described by the frequency of weather types defined by the type of circulation, mean daily air temperature, and the occurrence of rain. The variation in these factors affected the dynamics of the pollen season. The noteworthy frequency of days with rain and high seasonal sum of precipitation totals as well as the dominance of cyclonic weather from the westerly direction had an impact on the extension of the pollen season. The meteorological factors that directly affect pollen release and transport primarily include air humidity, expressed as vapour pressure (r > 0.3, p < 0.01), temperature(r from 0.2 to 0.4, p < 0.01). The relationships between averaged meteorological data and daily pollen concentration were stronger (r > 0.5, p < 0.01). Based on the correlation analysis, the meteorological variables were selected and regression equations were established using stepwise backward regression analysis.     

Trends in grass pollen season in southern Spain

The main characteristics of Poaceae pollen season at 8 sites in Andalusia were studied. Special attention was paid in the trends of grass pollen-season start and peak dates. Moreover, we analyse the intensity of the grass pollen season over the study period as well as potential temporal and spatial patterns in these data. Statistical analysis was performed to determine the possible influence of weather-related parameters on variations in the grass pollen season. Main results show an advance in the start and peak of grass pollen season and an increase in the annual Pollen Index and in the severity of the season (days > 25 pollen grains/m³). The future consequences of these changes in grass phenology could be related with changes in land use and also in pollinosis symptoms due to the higher concentrations recorded but also to the variations on pollen season dates.     

Long-term and short-term forecast models for Poaceae (grass) pollen in Poznań, Poland,constructed using regression analysis

Airborne concentrations of Poaceae pollen have been monitored in Poznań for more than 10 years and the length of the dataset is now considered sufficient for statistical analysis. The objective of this paper is to produce long-range forecasts that predict certain characteristics of the grass pollen season (such as the start, peak and end dates of the grass pollen season) as well as short-term forecasts that predict daily variations in grass pollen counts for the next day or next few days throughout the main grass pollen season. The method of forecasting was regression analysis. Correlation analysis was used to examine the relationship between grass pollen counts and the factors that affect its production, release and dispersal. The models were constructed with data from 1994 to 2004 and tested on data from 2005 and 2006. The forecast models predicted the start of the grass pollen season to within two days and achieved 61% and 70% accuracy on a scale of 1–4 when forecasting variations in daily average grass pollen counts in 2005 and 2006, respectively. This study has emphasised how important the weather during the few weeks or months preceding pollination is to grass pollen production, and draws attention to the importance of considering large-scale patterns of climate variability (indices of the North Atlantic Oscillation) when constructing forecast models for allergenic pollen.     

Pollen season and climate: Is the timing of birch pollen release in the UK approaching its limit?

In light of heightened interest in the response of pollen phenology to temperature, we investigated recent changes to the onset of Betula (birch) pollen seasons in central and southern England, including a test of predicted advancement of the Betula pollen season for London. We calculated onset of birch pollen seasons using daily airborne pollen data obtained at London, Plymouth and Worcester, determined trends in the start of the pollen season and compared timing of the birch pollen season with observed temperature patterns for the period 1995–2010. We found no overall change in the onset of birch pollen in the study period although there was evidence that the response to temperature was nonlinear and that a lower asymptotic start of the pollen season may exist. The start of the birch pollen season was strongly correlated with March mean temperature. These results reinforce previous findings showing that the timing of the birch pollen season in the UK is particularly sensitive to spring temperatures. The climate relationship shown here persists over both longer decadal-scale trends and shorter, seasonal trends as well as during periods of ‘sign-switching’ when cooler spring temperatures result in later start dates. These attributes, combined with the wide geographical coverage of airborne pollen monitoring sites, some with records extending back several decades, provide a powerful tool for the detection of climate change impacts, although local site factors and the requirement for winter chilling may be confounding factors.     

Exploring the spatio-temporal relationship between two key aeroallergens and meteorological variables in the United Kingdom

Constructing accurate predictive models for grass and birch pollen in the air, the two most important aeroallergens, for areas with variable climate conditions such as the United Kingdom, require better understanding of the relationships between pollen count in the air and meteorological variables. Variations in daily birch and grass pollen counts and their relationship with daily meteorological variables were investigated for nine pollen monitoring sites for the period 2000–2010 in the United Kingdom. An active pollen count sampling method was employed at each of the monitoring stations to sample pollen from the atmosphere. The mechanism of this method is based on the volumetric spore traps of Hirst design (Hirst in Ann Appl Biol 39(2):257–265, 1952). The pollen season (start date, finish date) for grass and birch were determined using a first derivative method. Meteorological variables such as daily rainfall; maximum, minimum and average temperatures; cumulative sum of Sunshine duration; wind speed; and relative humidity were related to the grass and birch pollen counts for the pre-peak, post peak and the entire pollen season. The meteorological variables were correlated with the pollen count data for the following temporal supports: same-day, 1-day prior, 1-day mean prior, 3-day mean prior, 7-day mean prior. The direction of influence (positive/negative) of meteorological variables on pollen count varied for birch and grass, and also varied when the pollen season was treated as a whole season, or was segmented into the pre-peak and post-peak seasons. Maximum temperature, sunshine duration and rainfall were the most important variables influencing the count of grass pollen in the atmosphere. Both maximum temperature (pre-peak) and sunshine produced a strong positive correlation, and rain produced a strong negative correlation with grass pollen count in the air. Similarly, average temperature, wind speed and rainfall were the most important variables influencing the count of birch pollen in the air. Both wind speed and rain produced a negative correlation with birch pollen count in the air and average temperature produced a positive correlation.     

Effect of meteorological parameters on Poaceae pollen in the atmosphere of Tetouan (NW Morocco)

Poaceae pollen is one of the most prevalent aeroallergens causing allergenic reactions. The aim of this study was to characterise the grass pollen season in Tetouan during the years 2008–2010, to analyse the effect of some meteorological parameters on the incidence of the airborne Poaceae pollen, and to establish forecasting variables for daily pollen concentrations. Aerobiological sampling was undertaken over three seasons using the volumetric method. The pollen season started in April and showed the highest pollen index in May and June, when the maximum temperature ranged from 23 to 27 °C, respectively. The annual pollen score recorded varied from year to year between 2,588 and 5,404. The main pollen season lasted 114–173 days, with peak days occurring mainly in May; the highest concentration reached 308 pollen grains/m³. Air temperature was the most important meteorological parameter and correlated positively to daily pollen concentration increase. An increase in relative humidity and precipitation was usually related to a decrease in airborne pollen content. External validation of the models performed using data from 2011 showed that Poaceae pollen concentration can be highly predicted (64.2–78.6 %) from the maximum temperature, its mean concentration for the same day in other years, and its concentration recorded on the previous day. Sensitive patients suffering allergy to Poaceae pollen are at moderate to highest risk of manifesting allergic symptoms to grass pollen over 33–42 days. The results obtained provide new information on the quantitative contribution of the Poaceae pollen to the airborne pollen of Tetouan and on its temporal distribution. Airborne pollen can be surveyed and forecast in order to warn the atopic population.     

Comparison of Alnus,Corylus, Betula pollen seasons in Riga,Moscow and Vilnius

Research characterizes differences and similarities of the seasonal behaviour of Alnus, Betula, Corylus pollen in Riga, Moscow and Vilnius. An important uniting factor dealing with the research is that on the selected territories in spring there are abundance of Alnus, Corylus and Betula airborne pollen. The study is based on the 2004–2011 atmospheric pollen records. Differences and similarities of the analysed territories include the following: (1) the beginning of the Alnus and Corylus pollen season usually coincided in Riga and Vilnius, whereas significantly differed between Riga and Moscow; (2) no significant differences among separate stations have been estimated concerning the beginning of the Betula pollen season; (3) Moscow differed by the shortest period of pollen season, independently of the pollen type; (4) the biennial cycle of Betula pollen is characteristic to Riga only; (5) in the spectrum of spring plants’ pollen, Corylus pollen was found in the least amount (10–23 pgm^?3 per day on the average); (6) average concentration of Betula pollen per day significantly differed in all locations of the survey, in Moscow, the concentration (853 pgm^?3) was twice higher that in Riga and Vilnius; (7) Alnus, Corylus and Betula pollen seasons overlap each other in all locations surveyed, thus creating additional load of pollen; (8) in each of the stations, there were 13–15 days when concentration of Betula pollen exceeded 100 pgm^?3.     

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

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.