Regional Importance of Alnus Pollen as an Aeroallergen: A Comparative Study of Alnus Pollen Counts from Worcester (UK) and Poznań (Poland)

Daily average Alnus pollen counts (1996-2005) from Worcester (UK) and Poznań (Poland) were examined with the aim of assessing the regional importance of Alnus pollen as an aeroallergen. The average number of Alnus pollen grains recorded annually at Poznań was more than 2.5 times that of Worcester. Furthermore, daily average Alnus pollen counts exceeded the thresholds of 100, 500 and 1,000 grains/m3 more times at Poznań than Worcester. Skin prick test results (1996-2005) and allergen-specific IgE(asIgE) measurements using the CAP (Pharmacia) system (2002-2005), were supplied by the Allergic Diseases Diagnostic Centre in Poznań. The annual number of positive skin prick tests to Alnus pollen allergens was significantly related (p<0.05) to seasonal variations in the magnitude of the Alnus pollen catch recorded at Poznań (r=0.70). The symptoms of patients with positive skin prick tests to Alnus pollen allergens were: 51% pollinosis, 43% atopic dermatitis, 4% asthma, 1% chronic urticaria and 1% eczema. On a scale of 0-6, 20.5% of patients examined for serum asIgE in relation to Alnus pollen allergens had asIgE measurements in classes 5 and 6. Alnus pollen is generally considered to be mildly allergenic. However, the amount of Alnus pollen released into the atmosphere in places such as Poznań may increase its impact on the population and make it one of the more important aeroallergens present.

A 30-Day-Ahead Forecast Model for Grass Pollen in North London, United Kingdom

A 30-day ahead forecast method has been developed for grass pollen at north London. The total period of the grass pollen season is covered by eight multiple regression models, each covering a 10-day period running consecutively from 21st May to 8th August. This means that three models were used for each 30-day forecast. The forecast models were produced using grass pollen and environmental data from 1961-1999 and tested on data from 2000 and 2002. Model accuracy was judged in two ways: the number of times the forecast model was able to successfully predict the severity (relative to the 1961-1999 dataset as a whole) of grass pollen counts in each of the eight forecast periods on a scale of one to four; and the number of times the forecast model was able to predict whether grass pollen counts were higher or lower than the mean. The models achieved 62.5% accuracy in both assessment years when predicting the relative severity of grass pollen counts on a scale of one to four, which equates to six of the eight 10-day periods being forecast correctly. The models attained 87.5% and 100% accuracy in 2000 and 2002 respectively when predicting whether grass pollen counts would be higher or lower than the mean. Attempting to predict pollen counts during distinct 10-day periods throughout the grass pollen season is a novel approach. The models also employed original methodology in the use of winter averages of the North Atlantic Oscillation to forecast 10-day means of allergenic pollen counts.

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.

Examining High Magnitude Grass Pollen Episodes at Worcester, United Kingdom, Using Back-Trajectory Analysis

Trajectory analysis is a valuable tool that has been used before in aerobiological studies, to investigate the movement of airborne pollen. This study has employed back-trajectories to examine the four highest grass pollen episodes at Worcester, during the 2001 grass pollen season. The results have shown that the highest grass pollen counts of the 2001 season were reached when air masses arrived from a westerly direction. Back-trajectory analysis has a limited value to forecasters because the method is retrospective and cannot be employed directly for forecasting. However, when used in conjunction with meteorological data this technique can be used to examine high magnitude events in order to identify conditions that lead to high pollen counts.

Temporal and Georaphical Variations in Grass Pollen Seasons in Areas of Western Europe: an Analysis of Season dates at Sites of the European Pollen Information System.

Geographical and temporal variations in the start dates of grass pollen seasons are described for selected sites of the European Pollen Information Service. Daily average grass pollen counts are derived from Network sites in Finland, the Netherlands, Denmark, United Kingdom, Austria, Italy and Spain, giving a broad longitudinal transect over Western Europe. The study is part of a larger project that also examines annual and regional variations in the severity, timing of the peak and duration of the grass pollen seasons. For several sites, data are available for over twenty years enabling long term trends to be discerned. The analyses show notable contrasts in the progression of the seasons annually with differing lag times occurring between southern and northern sites in various years depending on the weather conditions. The patterns identified provide some insight into geographical differences and temporal trends in the incidence of pollinosis. The paper discusses the main difficulties involved in this type of analysis and notes possibilities for using data from the European Pollen Information service to construct pan European predictive models for pollen seasons.

Comparison of Two Pollen Counting Methods of Slides from a Hirst Type Volumetric Trap.

Two of the most frequently used methods of pollen counting on slides from Hirst type traps are evaluated in this paper: the transverse traverse method and the longitudinal traverse method. The study was carried out during June–July 1996 and 1997 on slides from a trap at Worcester, UK. Three pollen types were selected for this purpose: Poaceae, Urticaceae and Quercus. The statistical results show that the daily concentrations followed similar trends (p < 0.01, R-values between 0.78–0.96) with both methods during the two years, although the counts were slightly higher using the longitudinal traverses method. Significant differences were observed, however, when the distribution of the concentrations during 24 hour sampling periods was considered. For more detailed analysis, the daily counts obtained with both methods were correlated with the total number of pollen grains for the taxon over the whole slide, in two different situations: high and low concentrations of pollen in the atmosphere. In the case of high concentrations, the counts for all three taxa with both methods are significantly correlated with the total pollen count. In the samples with low concentrations, the Poaceae and Urticaceae counts with both methods are significantly correlated with the total counts, but none of Quercus counts are. Consideration of the results indicates that both methods give a reasonable approximation to the count derived from the slide as a whole. More studies need be done to explore the comparability of counting methods in order to work towards a Universal Methodology in Aeropalynology.

Acute Asthma Epidemics, Weather and Pollen in England, 1987-1994

Recent epidemics of acute asthma have caused speculation that, if their causes were known, early warnings might be feasible. In particular, some epidemics seemed to be associated with thunderstorms. We wondered what risk factors predicting epidemics could be identified. Daily asthma admissions counts during 1987-1994, for two age groups (0-14 yrs and > or = 15 yrs), were measured using the Hospital Episodes System (HES). Epidemics were defined as combinations of date, age group and English Regional Health Authority (RHA) with exceptionally high asthma admission counts compared to the predictions of a log-linear autoregression model. They were compared with control days 1 week before and afterwards, regarding seven meteorological variables and 5 day average pollen counts for four species. Fifty six asthma epidemics were identified. The mean density of sferics (lightning flashes), temperature and rainfall on epidemic days were greater than those on control days. High sferics densities were overrepresented in epidemics. Simultaneously high sferics and grass pollen further increased the probability of an epidemic, but only to 15% (95% confidence interval 2-45%). Two thirds of epidemics were not preceded by thunderstorms. Thunderstorms and high grass pollen levels precede asthma epidemics more often than expected by chance. However, most epidemics are not associated with thunderstorms or unusual weather conditions, and most thunderstorms, even following high grass pollen levels, do not precede epidemics. An early warning system based on the indicators examined here would, therefore, detect few epidemics and generate an unacceptably high rate of false alarms.

Thunderstorm Related Asthma - the Epidemic of 24/25 June 1994

Background A large epidemic of asthma occurred following a thunderstorm in southern and central England on 24/25 June 1994. A collaborative study group was formed. Objectives To describe the epidemic and the meteorological, aerobiological and other environmental characteristics associated with it. Methods Collation of data from the Meteorological Office, the Pollen Research Unit, the Department of the Environment's Automatic Urban Network, from health surveillance by the Department of Health and the National Poisons Unit, from clinical experience in general practice and hospitals, and from an immunological study of some of the affected cases from north east London. Results The thunderstorm was a Mesoscale Convective System, an unusual and large form of storm with several centres and severe wind gusts. It occurred shortly after the peak grass pollen concentration in the London area. A sudden and extensive epidemic occurred within about an hour affecting possibly several thousand patients. Emergency services were stretched but the epidemic did not last long. Cases had high serum levels of IgE antibody to mixed grass pollen. Conclusion This study supports the view that patients with specific IgE to grass pollen are at risk of thunderstorm-related asthma. The details of the causal pathway from storm to asthma attack are not clear. Case-control and time series studies are being carried out.

Pollen Allergy in Cordoba City: Frequency of Sensitization and Relation with Antihistamine Sales

The occurrence of symptoms in pollen allergy patients in urban areas may be affected by local environmental factors such as sources of pollution, natural and ornamental vegetation, local architecture impeding dispersion, etc. The aim of this study was to analyse the frequency of sensitization in pollen allergy patients and the relationship with antihistamine sales. For this study, a large number of clinical records, together with pharmaceutical and pollen data, were collected between 1999 and 2001 in the city of Córdoba, in the south of the Iberian Peninsula. Differences were observed in the symptoms suffered by pollen allergy patients in different areas of the city due to varying local emission of both biological and non-biological particles. Temporal distribution of symptoms over the three study years was influenced by meteorological factors, especially rainfall patterns; higher water supply to plants was associated with increased airborne pollen concentrations. Air pollution might be one of the main factors affecting the distribution of pollen allergy patients within the city. Recent years have seen a worsening of symptoms and increased sensitization to urban species such as plane-trees.

Comparisons of Fungal Spore Distributions Using Air Sampling at Worcester, England (2006-2010)

This study determined annual and monthly fluctuations in concentration of 20 fungal genera. The selection of taxa was made based upon their high frequency in the air as well as their well-known allergenic properties. Air samples were collected using a spore trap of Hirst design at an urban site where the trap continuously worked throughout a 5-year survey. Weather data were acquired from a meteorological station co-located with the air sampler. Influence of several meteorological parameters was then examined to reveal species–environment interactions and the potential location of fungal spore sources within the urban area. The maximum monthly sum of mean daily spore concentration varied between genera, and the earliest peaks were recorded for Pleospora sp. in April and Ustilago sp. in June. However, the majority of investigated spore types occurred in the greatest concentrations between August and September. Out of the 20 studied taxa, the most dominant genus was Cladosporium sp., which exceeded an allergenic threshold of 3000 s m-3 40 times during very rainy years and twice as much during dry years. A Spearman’s rank test showed that statistically significant (p B 0.05) relationships between spore concentration and weather parameters were mainly rs B 0.50. Potential sources of spores at Worcester were likely to be localised outside the city area.

Field Evaluation of a Competitive Lateral-flow Assay for Detection of Alternaria brassicae in Vegetable Brassica Crops

On-site detection of inoculum of polycyclic plant pathogens could potentially contribute to management of disease outbreaks. A 6-min, in-field competitive immunochromatographic lateral flow device (CLFD) assay was developed for detection of Alternaria brassicae (the cause of dark leaf spot in brassica crops) in air sampled above the crop canopy. Visual recording of the test result by eye provides a detection threshold of approximately 50 dark leaf spot conidia. Assessment using a portable reader improved test sensitivity. In combination with a weather-driven infection model, CLFD assays were evaluated as part of an in-field risk assessment to identify periods when brassica crops were at risk from A. brassicae infection. The weather-driven model overpredicted A. brassicae infection. An automated 7-day multivial cyclone air sampler combined with a daily in-field CLFD assay detected A. brassicae conidia air samples from above the crops. Integration of information from an in-field detection system (CLFD) with weather-driven mathematical models predicting pathogen infection have the potential for use within disease management systems.

Diagnostic Tests and their Application in the Management of Soil- and Water-borne Oomycete Pathogen Species

Oomycete diseases cause significant losses across a broad range of crop and aquaculture commodities worldwide. These losses can be greatly reduced by disease management practices steered by accurate and early diagnoses of pathogen presence. Determinations of disease potential can help guide optimal crop rotation regimes, varietal selections, targeted control measures, harvest timings and crop post-harvest handling. Pathogen detection prior to infection can also reduce the incidence of disease epidemics. Classical methods for the isolation of oomycete pathogens are normally deployed only after disease symptom appearance. These processes are often-time consuming, relying on culturing the putative pathogen(s) and the availability of expert taxonomic skills for accurate identification; a situation that frequently results in either delayed application, or routine ‘blanket’ over-application of control measures. Increasing concerns about pesticides in the environment and the food chain, removal or restriction of their usage combined with rising costs have focussed interest in the development and improvement of disease management systems. To be effective, these require timely, accurate and preferably quantitatve diagnoses. A wide range of rapid diagnostic tools, from point of care immunodiagnostic kits to next generation nucleotide sequencing have potential application in oomycete disease management. Here we review currently-available as well as promising new technologies in the context of commercial agricultural production systems, considering the impacts of specific biotic and abiotic and other important factors such as speed and ease of access to information and cost effectiveness

Monitoring Infection Risk for Air and Soil Borne Fungal Plant Pathogens using Antibody and DNA Techniques and Mathematical Models describing Environmental Parameters

Economic losses resulting from disease development can be reduced by accurate and early detection of plant pathogens. Early detection can provide the grower with useful information on optimal crop rotation patterns, varietal selections, appropriate control measures, harvest date and post harvest handling. Classical methods for the isolation of pathogens are commonly used only after disease symptoms. This frequently results in a delay in application of control measures at potentially important periods in crop production. This paper describes the application of both antibody and DNA based systems to monitor infection risk of air and soil borne fungal pathogens and the use of this information with mathematical models describing risk of disease associated with environmental parameters.