Open AccessA demonstration project of Global Alliance against Chronic Respiratory Diseases: Prediction of interactions between air pollution and allergen exposure—the Mobile Airways Sentinel NetworK-Impact of air POLLution on Asthma and Rhinitis approach
Author(s) -
Mikhail Sofiev,
Yuliia Palamarchuk,
Annabelle Bédard,
Xavier Basagaña,
Josep M. Antó,
Rostislav Kouznetsov,
Rodrigo Delgado Urzua,
KarlChristian Bergmann,
João Fonseca,
Govert De Vries,
Michiel Van,
Isabella AnnesiMaesano,
Daniel Laune,
Jean Pépin,
Ingrid JullianDesayes,
Stéphane Zeng,
Wienczyslawa Czarlewski,
Jean Bousquet
Publication year - 2020
Publication title -
chinese medical journal/chinese medical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.537
H-Index - 63
eISSN - 2542-5641
pISSN - 0366-6999
DOI - 10.1097/cm9.0000000000000916
Subject(s) - air pollution , asthma , environmental health , air quality index , allergy , pollen , european union , medicine , business , immunology , meteorology , geography , ecology , chemistry , organic chemistry , economic policy , biology
This review analyzes the state and recent progress in the field of information support for pollen allergy sufferers. For decades, information available for the patients and allergologists consisted of pollen counts, which are vital but insufficient. New technology paves the way to substantial increase in amount and diversity of the data. This paper reviews old and newly suggested methods to predict pollen and air pollutant concentrations in the air and proposes an allergy risk concept, which combines the pollen and pollution information and transforms it into a qualitative risk index. This new index is available in an app (Mobile Airways Sentinel NetworK-air) that was developed in the frame of the European Union grant Impact of Air POLLution on sleep, Asthma and Rhinitis (a project of European Institute of Innovation and Technology-Health). On-going transformation of the pollen allergy information support is based on new technological solutions for pollen and air quality monitoring and predictions. The new information-technology and artificial-intelligence-based solutions help to convert this information into easy-to-use services for both medical practitioners and allergy sufferers.