Defining pollen exposure times for clinical trials of allergen immunotherapy for pollen‐induced rhinoconjunctivitis – an EAACI position paper

Abstract

Underlying principles in measuring pollen exposure and associated methodological problems and limitations were considered to achieve a consensus. Results: The Task Force achieved a comprehensive position in defining pollen exposure times for different pollen types. Definitions are presented for 'pollen season', 'high pollen season' (or 'peak pollen period') and 'high pollen days'. Conclusion: This EAACI position paper provides definitions of pollen exposures for different pollen types for use in AIT trials. Their validity as standards remains to be tested in future studies.

AeRobiology: The computational tool for biological data in the air

“…Nevertheless, the methods to calculate these parameters are subject to controversy (Bastl, Kmenta, & Berger, ) and the use of one or another method depends on the purpose and the type of bioaerosol (Jato et al, ). All the actual methods used to estimate the pollen season have been implemented in the calculate_ps function, obtaining easily the results about the phenological parameters and pollen intensity measurements (Andersen, ; Galán, García‐Mozo, Cariñanos, Alcázar, & Domínguez‐Vilches, ; Pfaar et al, ; Ribeiro, Cunha, & Abreu, ). Moreover, a new method is proposed for the first time in this package by the authors.…”

“…The users may perform numerous relevant calculations in the field of aerobiology, for example to calculate phenological parameters of the season or generate a calendar that represents the abundance and dynamics of the bioaerosols in the atmosphere. This example shows the calculation of the season (start, peak and end‐dates) for the Betula pollen season following the criterion proposed by Pfaar et al () for birch (Figure .3). Furthermore, Figure .4 shows the output of the calculation of the calendar using a violin plot design (O'Rourke, ): > plot_ps(munich_pollen, pollen.type = "Betula", year = 2011, method = "clinical", type = "birch") # Figure 1.3 > calendar.plot <‐ pollen_calendar(munich_pollen, method = "violinplot") # Figure 1.4 …”

“…;Galán, García-Mozo, Cariñanos, Alcázar, & Domínguez-Vilches, 2001;Pfaar et al, 2017;Ribeiro, Cunha, & Abreu, 2007). Moreover, a new method is proposed for the first time in this package by the authors.…”

Highlights and recent developments in airway diseases in EAACI journals (2018)

“…Similarly to chemical pollutants, the current pollen and spore monitoring stations have now been mapped, facilitating the access of information . The EAACI Task Force of the Immunotherapy and Aerobiology and Pollution Interest Group has defined pollen exposure times . The suggested criteria have been computationally validated by analyzing Poaceae pollen count data from up to 40 pollen monitoring stations between 2012 and 2016 .…”

“…63 The EAACI Task Force of the Immunotherapy and Aerobiology and Pollution Interest Group has defined pollen exposure times. 64 The suggested criteria have been computationally validated by analyzing Poaceae pollen count data from up to 40 pollen monitoring stations between 2012 and 2016. 65 There is a strong association between outdoor pollen levels and the number of asthma-related visits to the emergency department (ED) in children and adolescents aged <18 years, as recently demonstrated by a systematic review and meta-analysis.…”