POLLAR

Durada

January 2018 - December 2019

Coordinador

Jean Bousquet, Josep Mª Antó Boqué

Finançadors

EIT Health

Pàgina web

https://www.eithealth.eu/pollar

Interactions between air pollution, sleep and allergic diseases are insufficiently understood. POLLAR aims to provide an integrated software platform solution by combining emerging technologies with machine learning to:

• Understand effects of air pollution in allergic rhinitis and its impact on sleep, work, asthma
• Assess societal consequences, shared with citizen, corporate citizen and professionals
• Propose preventive strategies
• Develop participative policies

Objectives

Allergic rhinitis (AR) is impacted by allergens and air pollution. POLLAR will use a freely existing application for AR monitoring tested in 20 countries (Allergy Diary, IOS and Android, 5,000 users, TLR8) combined with a new tool allowing queries on allergen and pollen (TLR2) and existing pollution data. Using machine learning, the project will assess the relationship between air pollution and AR, through comparisons of polluted and non-polluted areas in six EU countries. Data generated in 2018 will be confirmed in 2019 and extended with the individual assessment of pollution (portable sensor, TLR6) in AR and sleep apnea patients, who will be used as a control group of impaired sleep. The geographic information system GIS will map the results. Consequences on quality of life (EQ-5D), asthma, school, work and sleep will be monitored and disseminated toward the population.

The impacts of POLLAR will be to:

• Propose novel care pathways integrating pollution and patient's literacy; study sleep;
• Improve work productivity;
• Propose the basis for a sentinel network at the EU level for pollution and allergy;
• Assess the societal implications of the interaction.

Target Group

More than 150 million people have allergic rhinitis (AR) in Europe and around 30% have uncontrolled AR during allergen exposure. Air pollution is extremely common. For industry, the link between AR/pollution and work productivity underpins the importance of prediction, prevention, diagnosis, treatment and patient compliance. For the public, prediction of AR/pollution interactions is needed. For healthcare organisations, prevention, diagnosis and effective treatments are essential.

Total funding

1,950,163 euros