Unusually high birch (Betula spp.) pollen concentrations in Poland in 2016 related to long-range transport (LRT) and the regional pollen occurrence

In 2016, the highest birch (Betula spp.) pollen concentrations were recorded in Krakow (Poland) since the beginning of pollen observations in 1991. The aim of this study was to ascertain the reason for this phenomenon, taking the local sources of pollen in Poland and long-range transport (LRT) episodes associated with the pollen influx from other European countries into account. Three periods of higher pollen concentrations in Krakow in 2016 were investigated with the use of pollen data, phenological data, meteorological data and the HYSPLIT numerical model to calculate trajectories up to 4 days back (96 h) at the selected Polish sites. From 5 to 8 April, the birch pollen concentrations increased in Krakow up to 4000 Pollen/m(3), although no full flowering of birch trees in the city was observed. The synoptic situation with air masses advection from the South as well as backward trajectories and the general birch pollen occurrence in Europe confirm that pollen was transported mainly from Serbia, Hungary, Austria, the Czech Republic, Slovakia, into Poland. The second analyzed period (13-14 April) was related largely to the local flowering of birches, while the third one in May (6-7 May) mostly resulted from the birch pollen transport from Fennoscandia and the Baltic countries. Unusual high pollen concentrations at the beginning of the pollen season can augment the symptomatic burden of birch pollen allergy sufferers and should be considered during therapy. Such incidents also affect the estimation of pollen seasons timing and severity.</p

How to do a clinical trial? Recommendations from the aerobiological point of view

Background: Allergy immunotherapy is still the only treatment of pollen allergy, providing a long-term effect. Clinical trials with pollen allergic patients are in need of validated, high quality pollen data and forecasts in order to grant comparability and to adhere to scientific standards. The aerobiological part of clinical trials remained hitherto not well defined, leaving the definition and use of pollen and forecast data more or less open. Methods: Pollen data of eight Austrian pollen-monitoring stations were selected and used as an example to present a new method of pollen data replacement, in case of station failure. Gower's similarity provides an objective calculation based on a defined time frame and a specific aeroallergen (for example birch, grass, mugwort and ragweed). Results: The ideal planning of the aerobiological part of a clinical trial with a pollen extract is described in detail with specific recommendations concerning site selection, pollen and forecast data, definition of the pollen season, and risk management. A checklist for every clinical trial with an aerobiological part was developed. Conclusion: Virtual biogeographic regions are beneficial due to their objective establishment, and can be integrated into clinical trials. Pollen data is not the same as forecast data. Both datasets have to be critically evaluated by trained aerobiologists before they are used in clinical trials. Therefore, only institutions with aerobiological knowledge, at best ISO-certified, should be involved in clinical trials and handle the aerobiological tasks. Keywords: Pollen data, Aerobiology, Allergen immunotherapy, Clinical trials, Checklis

Journal of Medical Internet Research / Evaluation of Pollen Apps Forecasts: The Need for Quality Control in an eHealth Service

Background: Pollen forecasts are highly valuable for allergen avoidance and thus raising the quality of life of persons concerned by pollen allergies. They are considered as valuable free services for the public. Careful scientific evaluation of pollen forecasts in terms of accurateness and reliability has not been available till date. Objective: The aim of this study was to analyze 9 mobile apps, which deliver pollen information and pollen forecasts, with a focus on their accurateness regarding the prediction of the pollen load in the grass pollen season 2016 to assess their usefulness for pollen allergy sufferers. Methods: The following number of apps was evaluated for each location: 3 apps for Vienna (Austria), 4 apps for Berlin (Germany), and 1 app each for Basel (Switzerland) and London (United Kingdom). All mobile apps were freely available. Todays grass pollen forecast was compared throughout the defined grass pollen season at each respective location with measured grass pollen concentrations. Hit rates were calculated for the exact performance and for a tolerance in a range of 2 and 4 pollen per cubic meter. Results: In general, for most apps, hit rates score around 50% (6 apps). It was found that 1 app showed better results, whereas 3 apps performed less well. Hit rates increased when calculated with tolerances for most apps. In contrast, the forecast for the “readiness to flower” for grasses was performed at a sufficiently accurate level, although only two apps provided such a forecast. The last of those forecasts coincided with the first moderate grass pollen load on the predicted day or 3 days after and performed even from about a month before well within the range of 3 days. Advertisement was present in 3 of the 9 analyzed apps, whereas an imprint mentioning institutions with experience in pollen forecasting was present in only three other apps. Conclusions: The quality of pollen forecasts is in need of improvement, and quality control for pollen forecasts is recommended to avoid potential harm to pollen allergy sufferers due to inadequate forecasts. The inclusion of information on reliability of provided forecasts and a similar handling regarding probabilistic weather forecasts should be considered.(VLID)486420

World Allergy Organization Journal / The evaluation of pollen concentrations with statistical and computational methods on rooftop and on ground level in Vienna How to include daily crowd-sourced symptom data

Background It is recommended to position pollen monitoring stations on rooftop level to assure a large catchment area and to gain data that are representative for a regional scale. Herein, an investigation of the representativeness of pollen concentrations was performed for 20 pollen types in the pollen seasons 20152016 in Vienna for rooftop and ground level and was compared with weather data and for the first time with symptom data. Methods The complete data set was analyzed with various statistical methods including Spearmen correlation, ANOVA, KolmogorovSmirnov test and logistic regression calculation: Odds ratio and Yule's Q values. Computational intelligence methods, namely Self Organizing Maps (SOMs) were employed that are capable of describing similarities and interdependencies in an effective way taking into account the U-matrix as well. The Random Forest algorithm was selected for modeling symptom data. Results The investigation of the representativeness of pollen concentrations on rooftop and ground level concerns the progress of the season, the peak occurrences and absolute quantities. Most taxa examined showed similar patterns (e.g. Betula), while others showed differences in pollen concentrations exposure on different heights (e.g. the Poaceae family). Maximum temperature, mean temperature and humidity showed the highest influence among the weather parameters and daily pollen concentrations for the majority of taxa in both traps. Conclusion The rooftop trap was identified as the more adequate one when compared with the local symptom data. Results show that symptom data correlate more with pollen concentrations measured on rooftop than with those measured on ground level.(VLID)490428

The connection of pollen concentrations and crowd-sourced symptom data: new insights from daily and seasonal symptom load index data from 2013 to 2017 in Vienna

Abstract Background Online pollen diaries and mobile applications nowadays allow easy and fast documentation of pollen allergy symptoms. Such crowd-sourced symptom data provides insights into the development and the onset of a pollen allergy. Hitherto studies of the symptom load index (SLI) showed a discrepancy between the SLI and the total pollen amount of a season, but did not analyze the daily data. Methods The Patient’s Hayfever Diary (PHD) was used as data pool for symptom data. Symptom data of Vienna (Austria) was chosen as a large and local sample size within the study period of 2013 until 2017. The city was divided into three different areas based on equal population densities and different environmental factors. Correlation factors, regression lines, locally weighted smoothing (LOESS) curves and line plots were calculated to examine the data. Results Daily SLI and pollen concentration data correlates well and the progress of the SLI within a pollen season is mirrored by the pollen concentrations. The LOESS curves do not deviate much from the regression line and support the linearity of the symptom-pollen correlation on a daily basis. Seasonal SLI data does not follow the same pattern as the respective seasonal pollen indices. Results did not vary in the three areas within Vienna or when compared with the Eastern region of Austria showing no significant spatial variation of the SLI. Discussion Results indicate a linear relationship of the SLI and pollen concentrations/seasonal polllen index (SPIn) on a daily basis for both in general and throughout the season, but not on a seasonal basis. These findings clarify the frequent misinterpretation of the SLI as index that is tightly connected to pollen concentrations, but reflects as well the seasonal variation of the burden of pollen allergy sufferers. Conclusion More than just the seasonal pollen index has to be considered when the SLI of a selected pollen season has to be explained. Cross-reactivity to other pollen types, allergen content and air pollution could play a considerable role. The similar behavior of the SLI in Vienna and a whole region indicate the feasibility of a possible symptom forecast in future and justifies the use of a single pollen monitoring station within a city of the size of Vienna

Defining Pollen Seasons : Background and Recommendations

Purpose of Review The definition of a pollen season determines the start and the end of the time period with a certain amount of pollen in the ambient air. Different pollen season definitions were used for a long time including the use of different terms for data and methods used to define a pollen season. Recently suggested pollen season definitions for clinical trials were tested and applied for the first time to more aeroallergens. Recent Findings This is a review on pollen season definitions and the latest recommendations. Recently, proposed terminology in aerobiology is promoted here in order to support reproducibility and repeatability in research. Two pollen season definitions, one based on percentages and one based on pollen concentrations, were tested. Summary Percentage definitions can be recommended for standard aerobiological routines and for retrospective applications, whereas pollen concentrations definitions can be recommended for prospective applications such as clinical trials.(VLID)361609