Anto, Josep M

Bousquet, Jean

D'Amato, Genaro

Hellings, Peter W

Mösges, Ralf

O'Hehir, Robyn E

Sheikh, Aziz

Van Eerd, Michiel

English

D'Amato, Gennaro

Mösges, Ralph

Hellings, Peter

Lirias

Journal of Allergy and Clinical Immunology

Assessment of thunderstorm-induced asthma using Google Trends

O'Hehir, Robyn E.

Anto, Josep M.

d'Amato, Gennaro

Hellings, Peter W.

van Eerd, Michiel

HAL: Hyper Article en Ligne

Hal-Diderot

Jean Bousquet

Robyn E. O'Hehir

Josep M. Anto

Gennaro D'Amato

Ralph Mösges

Peter W. Hellings

Michiel Van Eerd

Aziz Sheikh

Crossref

Archive Ouverte en Sciences de l'Information et de la Communication

Antó i Boqué, Josep Maria

UPF Digital Repository

An asthma outbreak of hospitalizations and deaths was noticed in Australia (November 2016) and in Kuwait (December 2016). This outbreak was clearly demonstrated using Google Trends (GT), a Web-based surveillance tool of interest in clinical practice.</p

Edinburgh Research Explorer

     Edinburgh Research Explorer                                      Assessment of thunderstorm-induced asthma using GoogleTrendsCitation for published version:Bousquet, J, O'Hehir, RE, Anto, JM, D'Amato, G, Mösges, R, Hellings, PW, Van Eerd, M & Sheikh, A 2017,'Assessment of thunderstorm-induced asthma using Google Trends', Journal of Allergy and ClinicalImmunology. https://doi.org/10.1016/j.jaci.2017.04.042Digital Object Identifier (DOI):10.1016/j.jaci.2017.04.042Link:Link to publication record in Edinburgh Research ExplorerDocument Version:Peer reviewed versionPublished In:Journal of Allergy and Clinical ImmunologyGeneral rightsCopyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s)and / or other copyright owners and it is a condition of accessing these publications that users recognise andabide by the legal requirements associated with these rights.Take down policyThe University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorercontent complies with UK legislation. If you believe that the public display of this file breaches copyright pleasecontact openaccess@ed.ac.uk providing details, and we will remove access to the work immediately andinvestigate your claim.Download date: 11. May. 2020Accepted ManuscriptAssessment of thunderstorm-induced asthma using Google TrendsJean Bousquet, MD, Robyn E. O’Hehir, MD, Josep M. Anto, MD, Genaro D’Amato,MD, Ralf Mösges, MD, Peter W. Hellings, MD, Michiel Van Eerd, PhD, Aziz Sheikh,MDPII: S0091-6749(17)30855-2DOI: 10.1016/j.jaci.2017.04.042Reference: YMAI 12837To appear in: Journal of Allergy and Clinical ImmunologyReceived Date: 6 January 2017Revised Date: 17 March 2017Accepted Date: 4 April 2017Please cite this article as: Bousquet J, O’Hehir RE, Anto JM, D’Amato G, Mösges R, Hellings PW,Van Eerd M, Sheikh A, Assessment of thunderstorm-induced asthma using Google Trends, Journal ofAllergy and Clinical Immunology (2017), doi: 10.1016/j.jaci.2017.04.042.This is a PDF file of an unedited manuscript that has been accepted for publication. As a service toour customers we are providing this early version of the manuscript. The manuscript will undergocopyediting, typesetting, and review of the resulting proof before it is published in its final form. Pleasenote that during the production process errors may be discovered which could affect the content, and alllegal disclaimers that apply to the journal pertain.MANUSCRIPT ACCEPTEDACCEPTED MANUSCRIPT 1 Assessment of thunderstorm-induced asthma using Google Trends 1  2 Jean Bousquet 1,2,MD Robyn E O’Hehir 3,MD Josep M Anto 4,MD Genaro D’Amato 5,MD Ralf Mösges 3 6,MD Peter W. Hellings 7,MD Michiel Van Eerd 8,PhD Aziz Sheikh 9 MD 4  5  6  7  8 1. MACVIA-France, Contre les MAladies Chroniques pour un VIeillissement Actif en France, European 9 Innovation Partnership on Active and Healthy Ageing Reference Site, Montpellier, France  10 2. INSERM U 1168, VIMA : Ageing and chronic diseases. Epidemiological and public health approaches, 11 Villejuif, Université Versailles St-Quentin-en-Yvelines, UMR-S 1168, Montigny le Bretonneux, France 12 3. Department of Allergy, Immunology and Respiratory Medicine, Alfred Hospital and Central Clinical School, 13 Monash University, Melbourne, Victoria, Australia; Department of Immunology, Monash University, 14 Melbourne, Victoria, Australia  15 4. ISGLoBAL, Centre for Research in Environmental Epidemiology (CREAL), Barcelona; IMIM (Hospital del Mar 16 Research Institute); CIBER Epidemiología y Salud Pública (CIBERESP), & Universitat Pompeu Fabra  (UPF), 17 Barcelona, Spain  18 5. Division of Respiratory and Allergic Diseases,Hospital 'A. Cardarelli', University of Naples Federico II, Italy  19 6. Institute of Medical Statistics, Informatics and Epidemiology, Medical Faculty, University of Cologne, 20 Germany  21 7. Laboratory of Clinical Immunology, Department of Microbiology and Immunology, KU Leuven, Leuven, 22 Belgium  23 8. Peercode DV, The Netherlands 24 9. Asthma UK Centre for Applied Research, Centre of Medical Informatics, Usher Institute of Population Health 25 Sciences and Informatics, The University of Edinburgh,  Edinburgh, UK  26  27  28  29  30  31 Short title: Google Trends in asthma 32  33 Address for correspondence 34 Professor Jean Bousquet   35 CHU Arnaud de Villeneuve, 371 Avenue du Doyen Gaston Giraud, 34295 Montpellier Cedex 5, 36 France      Tel +33 611 42 88 47    jean.bousquet@orange.fr 37   38 MANUSCRIPT ACCEPTEDACCEPTED MANUSCRIPT 2 Capsule summary 1 An asthma outbreak of hospitalizations and deaths was noticed in Australia (November 2016) and in 2 Kuwait (December 2016). This outbreak was clearly demonstrated using Google Trends (GT), a Web-3 based surveillance tool of interest in clinical practice. 4  5  6 Key words: Allergy, Asthma, Google Trends, Pollen, Rhinitis, Thunderstorm 7  8 Abbreviations 9  10 GT: Google Trends 11 EU: European Union 12 UK: United Kingdom  13 USA: United States of America 14  15  16  17  18 Word count: 1012  19 MANUSCRIPT ACCEPTEDACCEPTED MANUSCRIPT 3  To the editor 1 Google Trends (GT), a Web-based surveillance tool, uses Google to explore the searching trends of 2 specific queries. GT may predict the outbreak of many diseases. In Germany, correlations between the 3 patient-based, combined symptom medication score and GT data are stronger than those with the 4 regionally-measured pollen count data 1. Search activities using GT for terms such as "allergy," 5 "allergies," and "pollen" correlate strongly with observed pollen counts 2,3. GT reflects the real-world 6 epidemiology of symptomatic allergic rhinitis and could potentially be used to monitor allergic 7 rhinitis4.  Seasonality of allergic rhinitis was found using Internet searches and correlated with pollen 8 counts 3. Twitter data, Google search interests, and environmental sensor data can also be used to 9 predict the number of asthma-related emergency department visits in an area 5. 10 Studies on thunderstorm-induced asthma have convincingly shown that grass pollen can induce severe 11 asthma exacerbations when climatic conditions and pollen exposure are associated 6,7. It is possible 12 that such outbreaks can be observed using GT. Two recent outbreaks with several asthma deaths were 13 observed in Melbourne, Australia, November 20, 2016 and in Kuwait, December 2, 2016. 14 In the present study, we used GT to compare terms related to asthma, allergy and rhinitis in 10 15 countries from 2004 to December 20, 2016. The aims of the study were (i) to assess whether GT could 16 report the recent thunderstorm asthma outbreak in Australia and Kuwait; (ii) to determine whether 17 such an outbreak could be found in other countries over the past 13 years.  18 Methods 19 The following terms were used: “rhinitis”, “allergic rhinitis”, “hay fever”, “asthma”, “pollen”, 20 “allergy” (disease and term). However, only “allergy”, “allergic rhinitis”, “asthma” and “pollen” were 21 analyzed since “rhinitis” as a term or “hay fever” were labeled as “allergic rhinitis disease”. Only 22 “diseases” and “subjects” are translated by GT whereas “terms” are not translated. Major anti-rhinitis 23 (e.g. Loratadine, Cetirizine) or anti-asthma (e.g. Salbutamol, Seretide) medications were studied. 24 Intra-nasal and inhaled corticosteroids could not be differentiated using GT and were not used in the 25 study. 26 We examined GT queries from January 1, 2004 (starting date of GT) to December 20, 2016 for “all 27 countries” and from January 2011 to December 20, 2016 for the five most populated European Union 28 (EU) countries (i.e. France, Germany, Italy, Spain, United Kingdom (UK)), as well as Australia, 29 Canada, New Zealand and the USA. Only temperate and continental climatic zone countries  were 30 studied, as allergen exposure may vary with other climatic zones. We added Kuwait, as a severe 31 thunderstorm-induced asthma outbreak occurred December 2, 2016.  32 The prediction of the asthma outbreak using “allergic rhinitis”, “allergy”, “pollen” or “rhinitis 33 medications” queries was not tested since a more detailed analysis should be carried out focusing on 34 the region of the thunderstorm.  35 Results 36 When the trends for “all countries” were analyzed over the 13-year survey, the yearly trends were 37 comparable for the four terms between years (Figure 1 online). Trends for “allergy” were far higher 38 than for the other terms. Peaks were identified for “allergy” and “hay fever” but there was no clear 39 trend for asthma. Seasonal trends were observed for “Cetirizine”, “Loratadine” and “Fexofenadine” 40 MANUSCRIPT ACCEPTEDACCEPTED MANUSCRIPT 4 from 2008 to 2016 (Figure 2 online). On the other hand, there was no seasonality trend for asthma 1 linked with “allergy”, “pollen” or “allergic rhinitis” terms or for anti-asthma medications.  2 When the trends for the different countries were analyzed, GT was able to clearly demonstrate a sharp 3 and extremely important increase of “asthma” queries in Australia (Figures 1A and 1B) and Kuwait 4 (Figures 2A and 2B). The peak of queries started on the day of the asthma outbreak and asthma 5 queries returned to baseline within three weeks. There was no association between “asthma” and 6 “asthma medication” queries.  7 The examination of trends from 2004 to 2016 showed no other apparent peak of asthma queries using 8 GT from 2004 to December 20, 2016 in the eight other countries selected (Figure 3 online). However, 9 the analysis of the 5-year period (2011-2016) showed two peaks of asthma queries, one associated 10 with “allergic rhinitis”, “pollen” and/or “allergy” in New Zealand (November 2016) and a second 11 apparently independent (Figure 4 online).  The thunderstorm asthma outbreaks that occurred in Italy in 12 2004 and 2010, and in Australia in 2010 could not be identified using the country trends (13-, 5- and 13 1- year graphs). 14 Trends for asthma outbreaks were of similar importance to those for flu outbreaks in Australia and 15 Kuwait (Figure 5 online). 16 Discussion 17 Seasonality can be found using 13- and 5-year GT graphs for “allergy”, “hay fever”, “pollen” and H1-18 antihistamines. Some seasonality may be observed for asthma but it is independent of “allergy” or 19 “hay fever”. Asthma outbreaks can be clearly identified. 20 This study cannot avoid the possible misclassification of asthma, allergy and rhinitis, and reporting of 21 the terms differs between countries. The 5-year queries regarding “hay fever” and “pollen” differed 22 between countries and there may be country-specific queries. However, the same seasonal trends exist 23 for “allergy”, “hay fever”, “pollen” and “rhinitis medications”.    24 The 2016 Australia and Kuwait asthma outbreaks were clearly demonstrated using GT. Such a pattern 25 was also possibly found in New Zealand.  The thunderstorm asthma outbreaks that occurred in Italy in 26 2004 and 2010, and in Australia in 2010 could not be identified, probably because of the small number 27 of affected people. The asthma outbreak was at least more visible than flu. 28 Significant spikes in the Google search can be found with increased awareness of a disease by news 29 media and marketing media 8. In Europe, late December 2016, spikes for “allergy”, “asthma”, “pollen” 30 or “allergic rhinitis” were associated with the awareness of thunderstorm asthma in Australia and 31 Kuwait 9. 32 There is no correlation between “rhinitis” or “pollen” and “asthma” in any of the surveyed countries 33 except for the 2016 November asthma outbreak of Australia and possibly for one year in New 34 Zealand. On the other hand, the asthma outbreak of Kuwait appeared to be independent of “allergy”, 35 “hay fever” or “pollen”. This study shows that seasonal asthma can be identified by GT when there is 36 a severe asthma outbreak, but is not reported elsewhere. However, more precise analyses are needed to 37 investigate subtle trends. 38   39 MANUSCRIPT ACCEPTEDACCEPTED MANUSCRIPT 5 References 1  2 1. Konig V, Mosges R. A model for the determination of pollen count using google search queries 3 for patients suffering from allergic rhinitis. J Allergy (Cairo) 2014;2014:381983. 4 2. Willson TJ, Lospinoso J, Weitzel E, McMains K. Correlating regional aeroallergen effects on 5 internet search activity. Otolaryngol Head Neck Surg 2015;152:228-32. 6 3. Gaspar Marques J, Carreiro Martins P, Belo J, et al. Pollen Counts Influence Web Searches for 7 Asthma and Rhinitis. J Investig Allergol Clin Immunol 2016;26:192-4. 8 4. Kang MG, Song WJ, Choi S, et al. Google unveils a glimpse of allergic rhinitis in the real world. 9 Allergy 2015;70:124-8. 10 5. Ram S, Zhang W, Williams M, Pengetnze Y. Predicting asthma-related emergency department 11 visits using big data. IEEE J Biomed Health Inform 2015;19:1216-23. 12 6. Anto JM, Sunyer J. Thunderstorms: a risk factor for asthma attacks [editorial; comment]. Thorax 13 1997;52:669-70. 14 7. D'Amato G, Vitale C, D'Amato M, et al. Thunderstorm-related asthma: what happens and why. 15 Clin Exp Allergy 2016;46:390-6. 16 8. Scales D, Zelenev A, Brownstein JS. Quantifying the effect of media limitations on outbreak data 17 in a global online web-crawling epidemic intelligence system, 2008-2011. Emerg Health Threats 18 J 2013;6:21621. 19 9. Bousquet J, Agache I, Anto J, et al. Google Trends terms reporting rhinitis and related topics 20 differ in European countries. Allergy 2017;in press. 21  22  23 Jean Bousquet, MACVIA-France, Montpellier, France 24 Robyn O’Hehir, Department of Allergy, Immunology and Respiratory Medicine, Alfred Hospital and Central 25 Clinical School, Monash University, Melbourne, Victoria, Australia  26 Josep M Anto, ISGLoBAL, Centre for Research in Environmental Epidemiology (CREAL), Barcelona; IMIM 27 (Hospital del Mar Research Institute); CIBER Epidemiología y Salud Pública (CIBERESP), & Universitat 28 Pompeu Fabra  (UPF), Barcelona, Spain  29 Genaro D’Amato, Division of Respiratory and Allergic Diseases,Hospital 'A. Cardarelli', University of Naples 30 Federico II, Italy  31 Ralf Mösges, Institute of Medical Statistics, Informatics and Epidemiology, Medical Faculty, University of 32 Cologne, Germany    33 Peter W. Hellings , Laboratory of Clinical Immunology, Department of Microbiology and Immunology, KU 34 Leuven, Leuven, Belgium  35 Michiel Van Eerd, Peercode DV, The Netherlands 36 Aziz Sheikh, Asthma UK Centre for Applied Research, Centre of Medical Informatics, Usher Institute of 37 Population Health Sciences and Informatics, The University of Edinburgh,  Edinburgh, UK   38  39   40   41 MANUSCRIPT ACCEPTEDACCEPTED MANUSCRIPT 6 Figure 1: Queries reported by Google Trends in Australia  1 A: 5-year trend: January 1, 2004-December 20, 2016 2 B: 90-day trend: September 24-December 20, 2016 3  4 Figure 2: Queries reported by Google Trends in Kuwait 5 A: 5-year trend: January 1, 2004-December 20, 2016 6 B: 90-day trend: September 24-December 20, 2016 7 MANUSCRIPT ACCEPTEDACCEPTED MANUSCRIPTFigure 1 online: Queries reported by Google Trends in all countries (January 1, 2004 - December 20, 2016)     MANUSCRIPT ACCEPTEDACCEPTED MANUSCRIPTFigure 1A: Queries reported by Google Trends in Australia (January 1, 2004-December 20, 2016)   Figure 1B: Queries reported by Google Trends in Australia (September 24-December 20, 2016)  MANUSCRIPT ACCEPTEDACCEPTED MANUSCRIPTFigure 2 online: Google Trends for medication in all countries (January 1, 2004 –  December 20, 2016)   A- Antihistamines       B- Anti-asthma medications      MANUSCRIPT ACCEPTEDACCEPTED MANUSCRIPTFigure 2A: Queries reported by Google Trends in Kuwait (January 1, 2004-December 20, 2016)  Figure 2B: Queries reported by Google Trends in Kuwait (September 24-December 20, 2016)   MANUSCRIPT ACCEPTEDACCEPTED MANUSCRIPTFigure 3 online: Google searches (January 1, 2004 - 20 December 2016)    A- Canada   B- France   C- Germany   D- Italy  MANUSCRIPT ACCEPTEDACCEPTED MANUSCRIPT     E- New Zealand   F- UK  G- USA    MANUSCRIPT ACCEPTEDACCEPTED MANUSCRIPTFigure 4 online: Google searches (December 25, 2011 –  December 20, 2016)   All countries   A- Australia   B- Canada  C- Germany   MANUSCRIPT ACCEPTEDACCEPTED MANUSCRIPT      D-Italy   E- New Zealand   F- UK            MANUSCRIPT ACCEPTEDACCEPTED MANUSCRIPTG- USA   MANUSCRIPT ACCEPTEDACCEPTED MANUSCRIPT 1Figure 5 online: Google searches (January 4, 2012 –  December 27, 2016) 1  2 Australia 3  4  5 Kuwait 6  7  8 

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Assessment of thunderstorm-induced asthma using Google Trends

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