AIS LIFE 

State of the art and innovative aspects of the project

 

Since the 50s, pollen has been collected and counted following the method proposed by Hirst (1952). In most European countries, national pollen networks have been monitoring allergenic pollen and spores for years, providing health care providers and patients with pollen counts and forecasts. Networks are organised in the European Aeroallergen Network with over 350 pollen traps over Europe. Pollen recognition and counting is performed by qualified researchers through microscopic examinationof pollen slides (Lacey & West, 2006). This method is labour intensive and requires extensive trainingof researchers. Despite attempts to develop new methods for pollen monitoring (Chen et al, 2006;Ronneberger et al, 2002; Boucher et al, 2002; Zhang et al, 2005), pollen count is still the most frequently used method for assessment of exposure to pollen.

 

Pollen grain concentrations are monitored with numerous technological methods, employing manual,semi-manual or fully automated procedures, all aiming at: (a) recording various taxa of the pollen species present in a certain observation location, and (b) estimating the concentration of pollen grains(usually number of grains per cubic meter). In addition, observations coming from citizens report onsymptoms they are experiencing and the possible cause, thus helping to map the pollen influencewithin the population of an area of interest, and estimating the potential impact of pollen concentrations (e.g. the Dutch AllergieRadar system). Extended versions of such information systemsare in use in various EU countries and collect information on allergic symptoms and air pollen content,fostering information dissemination on the basis of personalised records. Another type of system currently under investigation and prototype development is based on Participatory Environmental Sensing (PES), where the individual takes part in recording environmental status, reporting on environmental conditions and pressures, and exchanging information of importance for his/her health status and concerns (Burke et al. 2006, Goldman et al. 2009, Karatzas, 2011).

 

Although pollen information has been disseminated for many years and doctors adapt therapeutic schemes to it, its effectiveness in terms of improved quality of life (QoL) and reduced medication use has been poorly studied. Some studies show that information about aeroallergens (e.g. allergenic airborne pollen grains and fungal spores) plays an important role in the timing of prophylactic medication and in maintaining compliance in treatments among the sensitised population (Bousquet etal. 2001; Sabbah et al. 1999; Stern et al. 1997).

 

Given the economic and social burden of allergic diseases (ref Bousquet J, Khaltaev N, Cruz AA, et al, in collaboration with the World HealthOrganization, GA(2)LEN and AllerGen. Allergic Rhinitis and its Impact on Asthma (ARIA) 2008 update. Allergy 2008;63,S86:8-160), pollen information represents a tool for reducing direct and indirect costs, in addition to improving patients’ QoL. Pollen information systems may be considered part of an Air Quality Information System (AQIS) andsome make use of internet technologies and SMS messaging for communicating information and provide warnings to recipients. However, dissemination of pollen information is not regulated and it has not been included in any legal text or guideline on atmospheric quality. Thus, pollen levels able to elicit symptoms (clinical thresholds) must be standardised in order to inform citizens on allergy risk and symptoms. High variability of those thresholds, as extensively reviewed by De Weger et al (Impact of Pollen” in “Allergenic Pollen”, eds Bergman and Sofiev, Springer, 2012) makes the identification of common or European levels of risk very difficult.

Information coverage can be: national, regional and personal (the latter being the goal of newly developed systems). Targeted information can be delivered to every subscribed user, including notifications of pollen data concerning user’s geographical area and alerts according his/her pollen sensitivity, sent directly by email, SMS or through particular ICT devices. Main information systems and services have been recently reviewed by Karatzas al (Presentation andDissemination of Pollen Information) in “Allergenic Pollen”, eds Bergman and Sofiev, Springer, 2012). In some systems, a meteorological model is combined with an air dispersion model, which takes input from pollen emission models (in some cases in combination with pollen emission observations), to calculate grains of pollen per cubic metre on a mean daily basis.

 

These computational information systems incorporate operational forecasting models, in order to provide predictions of pollen count levels for different forecasting horizons. In most cases, data come from public authorities from disperse observation stations, while others combine reports on allergy symptoms or pollen observations and flowers phenology, made by citizens with the use of ICT devices. In most cases, web-sites enriched with computational results are open to the general public, while some systems require further registration or even a fee to provide more detailed, personalised information.

 

At European level, Polleninfo is a web-based pollen information database, addressing national alerts and issues concerning pollen season, phenology, allergy risk, health recommendation and preventive measures. The platform provides pollen diary services where users can record daily allergy symptoms and compare this with current pollen load of the main allergenic plants. More recently, the SILAM forecasting model developed by the Finnish Meteorological Institute is able to publish forecasting maps about grass and birch pollen concentrations over certain geographical regions in Europe in a 5-day forecasting horizon. The system combines various phenological models describing pollination season of different pollen types, with meteorological and aerobiological information. All information is freely accessible but no specific notification /alert services are available.

 

The Danish Eulerian Hemispheric Model is another modelling system that supports pollen information provision. Several systems based
on the Participatory Environmental Sensing (PES), like the EDDMapS (Early Detection and Distribution Mapping System), the “What’s Invasive!” system, the Envitori project and the EnviObserver (have been developed in recent years.

Generally, the presentation of available data is made in an encoded and user-friendly manner (colourscaled graphs, short messages, static or dynamic maps, interactive, animated films), in order to overcome any misunderstandings in scientific terminology or confusions in sophisticated services. In a survey conducted in 2008 within COST Action ES0603, information from 19 EU countries on pollen information dissemination and the various dissemination media was collected. Results show that electronic media (mainly internet but also mobile phones) play an important role in the provision of pollen related information to citizens, thus demonstrating that a wide range of information channels are required to communicate with as many citizens as possible.

Although pollen information has been disseminated for several decades and ICT technology has increased quality and number of users, the effects of pollen information on QoL, symptoms, costs and efficacy of the allergy treatment has not been evaluated.

 

The AIS project demonstrates the clinical efficacy, cost-effectiveness and the additional value of a hightech system. In addition, implementation of pollen information with ultrafine particles measurements will be tested and validated on patients. Ability of ultrafine particulate to elicit a IgE response will be studied, in order to identify mechanisms underlying the role this type of pollutant plays in exacerbation of allergic rhinitis and asthma. It is worth mentioning that the EU Air Quality Directive does not mention allergenic air content among the harmful factors and sets no guidelines on public information about this component of air quality.

AIS shows:

1. Technological innovation: Technology has improved pollen forecasting and dissemination of pollen information. However, clinical impact of such information is still debated. AIS demonstrates, for the first time, if a high-tech system (web-based symptoms diary + smartphone application) is superior to a lowtech one (pollen bulletin) in terms of effectiveness in patients affected by allergic respiratory diseases. The system will include information on ultrafine particles, which represent a technological innovation in this field.

2. Innovation in processes and methods: well established methods for assessment of exposure to pollen and ultrafine particulate will be integrated for the first time. The effects of integrated information on QoL, symptoms, objective parameters and medication use will be evaluated. If one type of information or a combination of methods proves superior, a new pollen/pollutants information processing and dissemination will be available and applicable to any country. The rigorous design of the study can be applied to other types of environmental information systems aiming to reduce risks for human health.

3. Economic and business innovation: Although several applications for smartphone have been developed for information about environmental hazards for health in, none has been tested and validated for patients affected by allergic respiratory diseases. Once proved effective both from a clinical and a costeffectiveness point of view, the application will be further developed and disseminated, thus paving the way for new, permanent information systems and a continuous innovation of the model. With limited short-term mitigation measures against pollen exposure, facilitation of behavioural adaptation and preemptive medication of sensitive population is the most-important goal.