Development of personal pollen information—the next generation of pollen information and a step forward for hay fever sufferers

Pollen allergies affect a large part of the European population and are considered likely to increase. User feedback indicates that there are difficulties in providing proper information and valid forecasts using traditional methods of aerobiology due to a variety of factors. Allergen content, pollen loads, and pollen allergy symptoms vary per region and year. The first steps in challenging such issues have already been undertaken. A personalized pollen-related symptom forecast is thought to be a possible answer. However, attempts made thus far have not led to an improvement in daily forecasting procedures. This study describes a model that was launched in 2013 in Austria to provide the first available personal pollen information. This system includes innovative forecast models using bi-hourly pollen data, traditional pollen forecasts based on historical data, meteorological data, and recent symptom data from the patient’s hayfever diary. Furthermore, it calculates the personal symptom load in real time, in particular, the entries of the previous 5 days, to classify users. The personal pollen information was made available in Austria on the Austrian pollen information website and via a mobile pollen application, described herein for the first time. It is supposed that the inclusion of personal symptoms will lead to major improvements in pollen information concerning hay fever sufferers.     

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.     

Using meteorologic data to predict daily ragweed pollen levels

Pollen-related allergy is a common disease resulting in symptoms of hay fever and asthma. Control of symptoms depends (generally) on avoidance and pharmacological treatment. Both of these approaches could benefit from accurate predictions of pollen levels for future days. We have constructed a model that uses meteorological data to predict ragweed pollen levels based on air samples collected daily in Kalamazoo, MI from 1991 to 1994. Ragweed pollen counts were converted to pollen grains/m³ of air (24-h average). We used Poisson regression, which appropriately handles the heterogenous variance associated with pollen data. Using standard statistical model selection procedures, combined with biological considerations, we selected rainfall, wind speed, temperature, and the time measured from the start of the season as the most significant variables. Using our model, we propose a method that uses the weather forecast for the following day to predict the ragweed pollen level. This approach differs from most previous attempts because it uses Poisson regression and because this model needs to be fit iteratively each day. By updating the coefficients of the model based on the information to date, this method allows the fundamental shape of the pollen distribution curve to change from year to year. Application to the Kalamazoo data suggests that the method has good sensitivity and specificity for predicting high pollen days.     

Google Trends reflect allergic rhinitis symptoms related to birch and grass pollen seasons

Google Trends (GT) describes the variation of the relevant interest of internet searches toward medical conditions and related symptoms. Allergic rhinitis symptom levels result from the intensity of exposure to aeroallergens in combination with relevant medication use. We analyze data from Germany to examine the relationship between hay fever-related Google search terms, symptom levels, medication use, and pollen count levels. For doing so, we also employ the new definitions on pollen season and peak pollen period start and end as proposed by the European Academy of Allergy and Clinical Immunology in a recently published position paper. We extract GT data for a number of search terms related to allergic rhinitis for Germany. We use total nasal symptom and mediation scores as reported by patients via a patient hay fever diary in the Berlin and Brandenburg areas in Germany for 3 years (2014–2016), accompanied by pollen data. Then a Pearson and Spearman correlation analysis is performed between symptom data and GT data. A graphical analysis is conducted, and the identification of pollen season and peak pollen periods is done based on the EAACI criteria. The analysis reveals that GT data are highly correlated with symptom levels and follow peak pollen period start–end, concerning grass and birch pollen-induced allergic rhinitis symptoms. GT data can be used as a proxy for the identification of the onset and variation of nasal symptom and medication score for allergic rhinitis sufferers.     

Randomised double blind controlled clinical trial of intranasal budesonide in treatment of hay fever.

The effectiveness of budesonide, a new non-halogenated glucocorticoid administered by nasal inhaler, was evaluated in a double blind comparison with placebo in patients presenting with hay fever. Patients were supplied with antihistamine tablets and eye drops for use when they considered that their symptoms were inadequately controlled by their inhaler. Patients recorded the severity of their symptoms in a daily diary card and visited their general practitioner for assessment weekly for four weeks. All nasal symptoms of hay fever were appreciably reduced in the group taking budesonide and, although their eye symptoms were more severe than in the group taking placebo, they did not use appreciably more eye drops than the latter. The placebo group used appreciably more antihistamine tablets than those in the budesonide group. No patients were withdrawn from the budesonide group because of treatment failure or unacceptable side effects. The results suggest that budesonide is an acceptable and effective treatment for the nasal symptoms of hay fever.     

Seasonal distribution of pollen in the atmosphere of Darwin,tropical Australia: Preliminary results

Pollen loads in the atmosphere of Darwin, a city located in the wet‐dry tropics of Australia, have been monitored for the period March 2004 to November 2005 as part of a large research program looking at atmospheric particles and human health. Seven pollen types dominate the pollen spectrum, the herbaceous families of Poaceae (grasses) and Cyperaceae (sedges), as well as several native tree and shrub taxa, Acacia, Callitris, Casuarina, Arecaceae and Myrtaceae. The pollen loads were found to have a strong seasonal component associated with the alternating wet (November to March) and dry (April to October) seasons of the region. Seventy percent of the yearly pollen load is captured during the dry season, with the peak pollen period occurring at the onset of the dry season (April–May) when most grasses are in flower. The daily pollen concentration decreases as the dry season progresses, accompanied by a change in composition; fewer herbaceous but increasing woody taxa. Preliminary health outcomes reveal a positive association between hay fever, Poaceae and Acacia pollen, as well as a significant association between total fungal spore concentrations and asthma. The Darwin record contrasts significantly with surveys conducted in the subtropical and temperate cities of Australia where temperature as opposed to rainfall and the prevalence of northern hemisphere exotic tree species have a greater influence over the seasonality and composition of the pollen loads.     

First-line treatment of seasonal (ragweed) rhinoconjunctivitis: a randomized management trial comparing a nasal steroid spray and a nonsedating antihistamine

OBJECTIVE: To determine whether better health-related quality of life (HRQL) is achieved by initiating treatment of seasonal (ragweed) rhinoconjunctivitis (hay fever) with a nasal steroid (fluticasone) backed up by a nonsedating antihistamine (terfenadine) or whether it is better to start with the antihistamine and add the nasal steroid when necessary. DESIGN: Randomized, nonblind, parallel-group management study during the 6 weeks of the ragweed pollen season in 1995. PATIENTS: Sixty-one adults with ragweed pollen hay fever recruited from patients who had participated in previous clinical studies and from those who responded to notices in the local media. SETTING: Southern Ontario. INTERVENTIONS: Nasal steroid group: 200 micrograms of fluticasone nasal spray when needed (up to 400 micrograms/d) starting about 1 week before the ragweed pollen season and continued throughout, with 1 to 2 tablets of terfenadine daily (maximum 120 mg/d) if needed. Antihistamine group: 1 60-mg tablet of terfenadine when needed (maximum 120 mg/d) starting about 1 week before the ragweed pollen season and continued throughout, with 200-400 micrograms/d of fluticasone nasal spray (maximum 400 micrograms/d) if needed. OUTCOME MEASURES: HRQL before, at the height of and toward the end of the ragweed pollen season; HRQL was measured using the Rhinoconjunctivitis Quality of Life Questionnáire. RESULTS: Overall, HRQL tended to be better in the group of patients whose first-line treatment was with fluticasone (p = 0.052), but the difference between the 2 groups was small and not clinically important. Just over half (52% [16/31]) of the patients in the fluticasone group did not need additional help with terfenadine, whereas only 13% (4/30) of those in the terfenadine group did not need additional help with fluticasone (p = 0.002). CONCLUSIONS: There is little difference in the therapeutic benefit between the 2 approaches for the treatment of ragweed pollen hay fever. Therefore, the approach to treatment should be based on patient preference, convenience and cost. Regardless of the treatment, at least 50% of patients will need to take both types of medication in combination to control symptoms adequately.     

Airborne pollen survey of the warsaw area

Airborne and allergenic pollen types were identified in the area of Warsaw in the years 1983–1987. Over the same period of time, skin tests reactions were analysed in 400 hay fever patients. The aim of our study was to determine whether the most abundant pollen types at a given time did evoke hay fever symptoms in our allergy patients as confirmed by positive skin responses. In February, March and April 10.8% of patients showed allergy to deciduous tree pollen, while in May allergy to conifer pollen was confirmed in 2%. The most numerous group of patients demonstrating pollinosis due to grass and rye pollen attended the Clinic in June and July. In the autumn (September-October) symptoms due to weed pollens predominated in our patients.     

Trends in prevalence of allergic rhinitis and correlation with pollen counts in Switzerland

In recent decades, a large number of epidemiological studies investigating the change of prevalence of hay fever showed an increase in the occurrence of this disease. However, other studies carried out in the 1990s yielded contradictory results. Many environmental factors have been hypothesized to contribute to the increasing hay fever rate, including both indoor and ambient air pollution, reduced exposure to microbial stimulation and changes in diets. However, the observed increase has not convincingly been explained by any of these factors and there is limited evidence of changes in exposure to these risk factors over time. Additionally, recent studies show that no further increase in asthma, hay fever and atopic sensitisation in adolescents and adults has been observed during the 1990s and the beginning of the new century. As the pattern of pollen counts has changed over the years, partly due to the global warming but also as a consequence of a change in the use of land, the changing prevalence of hay fever might partly be driven by this different pollen exposure. Epidemiological data for hay fever in Switzerland are available from 1926 until 2000 (with large gaps between 1926 and 1958 and 1958 to 1986) whereas pollen data are available from 1969 until the present. This allows an investigation as to whether these data are correlated provided the same time spans are compared. It would also be feasible to correlate the pollen data with meteorological data which, however, is not the subject of our investigation. Our study focuses on analyzing time series of pollen counts and of pollen season lengths in order to identify their trends, and to ascertain whether there is a relationship between these trends and the changes in the hay fever prevalence. It is shown in this paper that the pollen exposure has been decreasing in Basel since the beginning of the 1990s whereas the rate of the hay fever prevalence in Switzerland remained approximately unchanged in this period but with a slight tendency to decrease. In Locarno, most of the pollen species also show a decreasing trend, while in Zurich, the development is somewhat different as the pollen counts of most of the pollen types have been increasing. It is interesting, however, that some of the pollen counts of this station (grass, stinging nettle, mugwort and ragweed) have been decreasing in the period 1982–2007.     

Time series predictions with neural nets: Application to airborne pollen forecasting

Pollen allergy is a common disease causing rhinoconjunctivitis (hay fever) in 5–10% of the population. Medical studies have indicated that pollen related diseases could be highly reduced if future pollen contents in the air could be predicted. In this work we have developed a new forecasting method that applies the ability of neural nets to predict the future behaviour of chaotic systems in order to make accurate predictions of the airborne pollen concentration. The method requires that the neural net be fed with non-zero values, which restricts the method predictions to the period following the start of pollen flight. The operational method outlined here constitutes a different point of view with respect to the more generally used forecasts of time series analysis, which require input of many meteorological parameters. Excellent forecasts were obtained training a neural net by using only the time series pollen concentration values.     

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.     

Seasonal non-allergic rhinoconjunctivitis

Several patients suffering from seasonal rhinitis imitating treepollen induced hay fever, but who have negative tests with pollen allergens, have been investigated. In a retrospective study, 86 such patients with seasonal non-allergic rhinitis (SNAR) were compared with two other groups of patients: patients with birch pollen hay fever (BP) and patients with vasomotor rhinitis (VR). It was found that SNAR and VR compared to BP started at a later age, was more common in females and less often combined with hypersensitivity against nuts, apples and stone fruits. Flowers and strong smells more often elicited symptoms in SNAR than in VR and BP. The seasonal symptoms started earlier among SNAR than among BP patients. Positive skin tests with common inhalant allergens were much more common in BP than in SNAR. It is concluded that SNAR has more characteristics in common with VR than with BP. A probable explanation of the disease is a non-specific hypersensitivity to non-allergenic substances occurring in out-door air in spring, possibly air pollutants bound to pollen grains.     

Allergenic airborne pollen monitoring of Vigo (NW Spain) in 1995–2001

Pollen data from the atmosphere of Vigo, NW Spain was collected using a Hirst type pollen trap over a seven-year period (1995–2001). A total of 56 different pollen types were identified, among which Urticaceae, Poaceae, Betula and Quercus represent the greatest risk for people suffering from allergic rhinitis (hay fever) or other allergic diseases. Although in the atmosphere of Vigo the presence of allergenic pollen is constant throughout the year, the months of March and April account for 40% of the annual total pollen count. Two main risk periods have been identified for asthma and allergies: (1) March – April, and (2) June – July, the latter is of greater importance due to high concentrations of Poaceae pollen. Correlation analysis with meteorological parameters demonstrates that rainfall, relative humidity, maximum temperature, sun hours and north-easterly winds are the main factors influencing the average daily pollen concentrations in the atmosphere.     

Incidence of allergic rhinitis in general practice, 1981-92.

OBJECTIVES--To determine the epidemiology of hay fever and to consider the role of pollution. DESIGN--Examination of data on weekly incidence of allergic rhinitis and hay fever by age, sex, region, and location. SETTING--Royal College of General Practitioners Weekly Returns Service. Practice data were based on registered populations of 220,000 in 1981, rising to 700,000 in 1992 from England and Wales. MAIN OUTCOME MEASURES--Numbers of new cases of hay fever and allergic rhinitis. Data on pollen counts for Darlington, Derby, and London. RESULTS--The incidence of allergic rhinitis fluctuated greatly from year to year but showed no trend. Peaks in hay fever coincided with peak pollen counts. No important differences were found between urban and rural locations or different parts of the country with respect to both size and timing of the peaks. Incidence was highest in children (5-14 years). CONCLUSIONS--The similarity of the results throughout England and Wales does not support an important role for local pollutants in hay fever. However, the possibility that levels of pollutants are high enough to act as an adjuvant in hay fever across the whole study area has not been excluded.     

Climate teleconnections and recent patterns of human and animal disease outbreaks

Background

Recent clusters of outbreaks of mosquito-borne diseases (Rift Valley fever and chikungunya) in Africa and parts of the Indian Ocean islands illustrate how interannual climate variability influences the changing risk patterns of disease outbreaks. Although Rift Valley fever outbreaks have been known to follow periods of above-normal rainfall, the timing of the outbreak events has largely been unknown. Similarly, there is inadequate knowledge on climate drivers of chikungunya outbreaks. We analyze a variety of climate and satellite-derived vegetation measurements to explain the coupling between patterns of climate variability and disease outbreaks of Rift Valley fever and chikungunya.

Methods and Findings

We derived a teleconnections map by correlating long-term monthly global precipitation data with the NINO3.4 sea surface temperature (SST) anomaly index. This map identifies regional hot-spots where rainfall variability may have an influence on the ecology of vector borne disease. Among the regions are Eastern and Southern Africa where outbreaks of chikungunya and Rift Valley fever occurred 2004–2009. Chikungunya and Rift Valley fever case locations were mapped to corresponding climate data anomalies to understand associations between specific anomaly patterns in ecological and climate variables and disease outbreak patterns through space and time. From these maps we explored associations among Rift Valley fever disease occurrence locations and cumulative rainfall and vegetation index anomalies. We illustrated the time lag between the driving climate conditions and the timing of the first case of Rift Valley fever. Results showed that reported outbreaks of Rift Valley fever occurred after ∼3–4 months of sustained above-normal rainfall and associated green-up in vegetation, conditions ideal for Rift Valley fever mosquito vectors. For chikungunya we explored associations among surface air temperature, precipitation anomalies, and chikungunya outbreak locations. We found that chikungunya outbreaks occurred under conditions of anomalously high temperatures and drought over Eastern Africa. However, in Southeast Asia, chikungunya outbreaks were negatively correlated (p<0.05) with drought conditions, but positively correlated with warmer-than-normal temperatures and rainfall.

Conclusions/Significance

Extremes in climate conditions forced by the El Niño/Southern Oscillation (ENSO) lead to severe droughts or floods, ideal ecological conditions for disease vectors to emerge, and may result in epizootics and epidemics of Rift Valley fever and chikungunya. However, the immune status of livestock (Rift Valley fever) and human (chikungunya) populations is a factor that is largely unknown but very likely plays a role in the spatial-temporal patterns of these disease outbreaks. As the frequency and severity of extremes in climate increase, the potential for globalization of vectors and disease is likely to accelerate. Understanding the underlying patterns of global and regional climate variability and their impacts on ecological drivers of vector-borne diseases is critical in long-range planning of appropriate disease and disease-vector response, control, and mitigation strategies.     

Effects of meteorological conditions on spore plumes

Fungal spores are an ever-present component of the atmosphere, and have long been known to trigger asthma and hay fever symptoms in sensitive individuals. The atmosphere around Tulsa has been monitored for airborne spores and pollen with Burkard spore traps at several sampling stations. This study involved the examination of the hourly spore concentrations on days that had average daily concentrations near 50,000 spores/m(3) or greater. Hourly concentrations of Cladosporium, Alternaria, Epicoccum, Curvularia, Pithomyces, Drechslera, smut spores, ascospores, basidiospores, other, and total spores were determined on 4 days at three sites and then correlated with hourly meteorological data including temperature, rainfall, wind speed, dew point, air pressure, and wind direction. On each of these days there was a spore plume, a phenomenon in which spore concentrations increased dramatically over a very short period of time. Spore plumes generally occurred near midday, and concentrations were seen to increase from lows around 20,000 total spores/m(3) to highs over 170,000 total spores/m(3) in 2 h. Multiple regression analysis of the data indicated that increases in temperature, dew point, and air pressure correlated with the increase in spore concentrations, but no single weather variable predicted the appearance of a spore plume. The proper combination of changes in these meteorological parameters that result in a spore plume may be due to the changing weather conditions associated with thunderstorms, as on 3 of the 4 days when spore plumes occurred there were thunderstorms later that evening. The occurrence of spore plumes may have clinical significance, because other studies have shown that sensitization to certain spore types can occur during exposure to high spore concentrations.     

Gramineae hay fever,and aerobiological and clinical investigation in Palermo; Sicily

Summary Epidemiological and aerobiological observations (1987;1989) have been carried out for three years in order to search the existing relationship between the Gramineae's daily pollen concentration in Palermo's atmosphere and the number of hay fever cases due to such pollen.The aerobiological data were obtained with a 2000 VPPS volumetric sampler. Clinical research was performed on 555 hay fever patients treated in our ambulatory over a three-year period (1987–1989).These data, elaborated by a seven day running mean method and correlated with epidemiological data, evidenced that three of the pollen families in our territory are clinically important: Urticaceae,Parietaria prevailing among them, Gramineae and Oleaceae,Olea europaea prevailing among them.The Gramineae are the second most important allergenic pollen (32,08% of all the pollinosis) whereas, as far as its concentration in the atmosphere is concerned; it ranks third followingParietaria and Oleaceae.     

Predicting the grass pollen count from meteorological data with regard to estimating the severity of hayfever symptoms in Melbourne (Australia)

In Melbourne, Australia, grass pollen is the predominant cause of hayfever in late spring and summer. The grass pollen season has been monitored in Melbourne, using a Burkard spore trap, for 13 years (1975–1981, 1985 and 1991–1997). Total counts for grass pollen were highly variable from one season to the next (approximately 1000 to >8000 grains/m³). The daily grass pollen counts also showed a high variability (0 to approximately 400 grains/m³). In this study, the grass pollen counts of the 13 years (12 grass pollen seasons, extending from October to January) have been compared with meteorological data in order to identify the conditions that can determine the daily amounts of grass pollen in the air. It was found that the seasonal total of grass pollen was directly correlated with the rainfall sum of the preceding 12 months (1 September–31 August): seasonal total of grass pollen (counts/m³)=18.161 × rainfall sum of the preceding 12 months (mm) −8541.5 (r _s=0.74,P<0.005,n=12). The daily amounts of grass pollen in the air were positively correlated with the corresponding daily average ambient temperatures (P<0.001). The daily amount of grass pollen which was to be expected with a certain daily average temperature was linked to the seasonal total of grass pollen: in years with high total grass pollen counts, a lower daily average temperature was required for a high daily pollen count than in years with low total grass pollen counts. As the concentration of airborne grass pollen determines the severity of hayfever in sensitive patients, an estimation of daily grass pollen counts can provide an indication of potential pollinosis symptoms. We compared daily grass pollen counts with the reported symptomatic responses of hayfever sufferers in November 1985 and found that hayfever symptoms were significantly correlated to the grass pollen counts (P<0.001 for nasal,P<0.005 for eye symptoms). Thus, a combination of meteorological information (i.e. rainfall and temperature) allows for an estimation of the potential daily pollinosis symptoms during the grass pollen season. Here we propose a symptom estimation chart, allowing a quick prediction of eye and nasal symptoms that are likely to occur as a result of variations in meteorological conditions, thus enabling both physicians and patients to take appropriate avoidance measures or therapy.     

Allergy symptoms in relation to alder and birch pollen concentrations in Finland

In order to study allergic people responding to daily changes in pollen concentrations, we compared personal diary data on allergic symptoms and the use of allergy medicines to daily pollen counts during the two unequal alder and birch pollen seasons of 2009 and 2010. Almost 90% of the 61 subjects with physician-diagnosed birch pollinosis developed conjunctival, nasal or other symptoms during the peak birch pollination. Most subjects (95%) also reported symptoms during the alder pollination. Despite a delay between the most severe symptoms and the pollen peaks and the increased risk of allergy symptoms between the alder and birch pollen peaks at much lower pollen concentrations, the number of subjects with allergy symptoms correlated with the daily pollen concentrations in both years (r ₀₉ = 0.35, r ₁₀ = 0.36, p < 0.01). The positive correlation was even stronger (r ₀₉ = 0.69, r ₁₀ = 0.74, p < 0.001) in relation to the cumulative sum of daily concentrations. The use of allergy medicines precisely followed the abundance of allergy symptoms in both years (r ₀₉ = 0.96, r ₁₀ = 0.70, p < 0.001). We conclude that there is a fair correlation between the daily allergy symptoms and the particular pollen concentrations, but the risk of developing symptoms at low, moderate and high concentrations is affected by the progression of the pollen season.     

The influence of temperature,relative humidity and rainfall on the occurrence of pollen allergens (Betula,Poaceae, Ambrosia artemisiifolia) in the atmosphere of Bratislava (Slovakia)

The occurrence of pollen grains in the atmosphere markedly relates to meteorological factors. In the study we have evaluated a correlation between the concentration of pollen grains in the atmosphere of Bratislava and temperature, relative humidity and rainfall during the vegetation period of 1995 and 1997. For our analysis we have selected one representative of each phytoallergen group (trees, grasses, weeds). We have chosen the Betula genus of trees, the whole Poaceae family of grasses and ragweed Ambrosia artemisiifolia L. to represent weeds. The taxons mentioned represent the most significant allergens in Slovakia. The concentration of pollen grains has been monitored by a Lanzoni volumetric pollen trap. The data obtained, the average daily concentration in 1 m(3), have been included in the statistical analysis together with values for the average daily temperature, relative humidity and total rainfall in 24 h. The correlation between the concentration of pollen grains in the atmosphere and selected meteorological variables from daily monitoring has been studied with the help of linear regression and correlation coefficients. We have found the average daily temperature and relative humidity (less than temperature) to be significant factors influencing the occurrence of pollen grains in the atmosphere of Bratislava. The total daily rainfall does not seem to be significant from the statistical point of view.