Literature DB >> 30942904

Google Trends and pollen concentrations in allergy and airway diseases in France.

Jean Bousquet1,2,3,4,5,6, Gabrielle L Onorato1, Gilles Oliver7, Xavier Basagana8,9,10, Isabella Annesi-Maesano11, Sylvie Arnavielhe12, Jean-Pierre Besancenot7, Isabelle Bosse13, Philippe J Bousquet14, Denis André Charpin15, D Caillaud16, Pascal Demoly17, Philippe Devillier18, Eve Mathieu-Dupas12, Jean-François M Fontaine19, Jocelyne Just20, Josep M Anto8,9,10,21, João Fonseca22,23, Uwe Berger24, Michel Thibaudon7.   

Abstract

BACKGROUND: Google Trends (GTs) is a web-based surveillance tool that explores the searching trends of specific queries via Google. This tool proposes to reflect the real-life epidemiology of allergic rhinitis and asthma. However, the validation of GTs against pollen concentrations is missing at the country level.
OBJECTIVES: In the present study, we used GTs (a) to compare the terms related to allergy in France, (b) to assess seasonal variations across the country for 5 years and (c) to compare GTs and pollen concentrations for 2016.
METHODS: Google Trends queries were initially searched to investigate the terms reflecting pollen and allergic diseases. 13- and 5-year GTs were used in France. Then, 5-year GTs were assessed in all metropolitan French regions to assess the seasonality of GTs. Finally, GTs were compared with pollen concentrations (Réseau National de Surveillance en Aerobiology) for 2016 in seven regions (GTs) and corresponding cities (pollen concentrations).
RESULTS: The combination of searches for "allergy" as a disease, "pollen" as a disease cause and "ragweed" as a plant was needed to fully assess the pollen season in France. "Asthma" did not show any seasonality. Using the 5-year GTs, an annual and clear seasonality of queries was found in all regions depending on the predicted pollen exposure for spring and a summer peak but not for winter peaks. The agreement between GT queries and pollen concentrations is usually poor except for spring trees and grasses. Moreover, cypress pollens are insufficiently reported by GTs.
CONCLUSIONS: Google Trends cannot predict the pollen season in France.
© 2019 EAACI and John Wiley and Sons A/S. Published by John Wiley and Sons Ltd.

Entities:  

Keywords:  allergy; asthma; google trends; pollen; rhinitis

Year:  2019        PMID: 30942904     DOI: 10.1111/all.13804

Source DB:  PubMed          Journal:  Allergy        ISSN: 0105-4538            Impact factor:   13.146


  3 in total

1.  Assessment of Google Trends terms reporting allergies and the grass pollen season in Ukraine.

Authors:  Igor Kaidashev; Halyna Morokhovets; Viktoriia Rodinkova; Lawrence DuBuske; Jean Bousquet
Journal:  World Allergy Organ J       Date:  2020-09-30       Impact factor: 4.084

Review 2.  Treatment of allergic rhinitis during and outside the pollen season using mobile technology. A MASK study.

Authors:  A Bédard; X Basagaña; J M Anto; J Garcia-Aymerich; P Devillier; S Arnavielhe; A Bedbrook; G L Onorato; W Czarlewski; R Murray; R Almeida; J A Fonseca; J Correia da Sousa; E Costa; M Morais-Almeida; A Todo-Bom; L Cecchi; G De Feo; M Illario; E Menditto; R Monti; C Stellato; M T Ventura; I Annesi-Maesano; I Bosse; J F Fontaine; N Pham-Thi; M Thibaudon; P Schmid-Grendelmeier; F Spertini; N H Chavannes; W J Fokkens; S Reitsma; R Dubakiene; R Emuzyte; V Kvedariene; A Valiulis; P Kuna; B Samolinski; L Klimek; R Mösges; O Pfaar; S Shamai; R E Roller-Wirnsberger; P V Tomazic; D Ryan; A Sheikh; T Haahtela; S Toppila-Salmi; E Valovirta; V Cardona; J Mullol; A Valero; M Makris; N G Papadopoulos; E P Prokopakis; F Psarros; C Bachert; P W Hellings; B Pugin; C Bindslev-Jensen; E Eller; I Kull; E Melén; M Wickman; G De Vries; M van Eerd; I Agache; I J Ansotegui; S Bosnic-Anticevich; A A Cruz; T Casale; J C Ivancevich; D E Larenas-Linnemann; M Sofiev; D Wallace; S Waserman; A Yorgancioglu; D Laune; J Bousquet
Journal:  Clin Transl Allergy       Date:  2020-12-09       Impact factor: 5.871

3.  Prediction of Asthma Hospitalizations for the Common Cold Using Google Trends: Infodemiology Study.

Authors:  Bernardo Sousa-Pinto; Jaana I Halonen; Aram Antó; Vesa Jormanainen; Wienczyslawa Czarlewski; Anna Bedbrook; Nikolaos G Papadopoulos; Alberto Freitas; Tari Haahtela; Josep M Antó; João Almeida Fonseca; Jean Bousquet
Journal:  J Med Internet Res       Date:  2021-07-06       Impact factor: 5.428

  3 in total

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