Prediction of asthma hospitalizations for the common cold using google trends: infodemiology study

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• dc.contributor.author Sousa Pinto, Bernardo
• dc.contributor.author Halonen, Jaana I.
• dc.contributor.author Antó, Aram
• dc.contributor.author Jormanainen, Vesa
• dc.contributor.author Czarlewski, Wienczyslawa
• dc.contributor.author Bedbrook, Anna
• dc.contributor.author Papadopoulos, Nikolaos
• dc.contributor.author Freitas, Alberto
• dc.contributor.author Haahtela, Tari
• dc.contributor.author Antó i Boqué, Josep Maria
• dc.contributor.author Almeida Fonseca, João
• dc.contributor.author Bousquet, Jean
• dc.date.accessioned 2021-08-05T05:57:46Z
• dc.date.available 2021-08-05T05:57:46Z
• dc.date.issued 2021
• dc.description.abstract Background: In contrast to air pollution and pollen exposure, data on the occurrence of the common cold are difficult to incorporate in models predicting asthma hospitalizations. Objective: This study aims to assess whether web-based searches on common cold would correlate with and help to predict asthma hospitalizations. Methods: We analyzed all hospitalizations with a main diagnosis of asthma occurring in 5 different countries (Portugal, Spain, Finland, Norway, and Brazil) for a period of approximately 5 years (January 1, 2012-December 17, 2016). Data on web-based searches on common cold were retrieved from Google Trends (GT) using the pseudo-influenza syndrome topic and local language search terms for common cold for the same countries and periods. We applied time series analysis methods to estimate the correlation between GT and hospitalization data. In addition, we built autoregressive models to forecast the weekly number of asthma hospitalizations for a period of 1 year (June 2015-June 2016) based on admissions and GT data from the 3 previous years. Results: In time series analyses, GT data on common cold displayed strong correlations with asthma hospitalizations occurring in Portugal (correlation coefficients ranging from 0.63 to 0.73), Spain (ρ=0.82-0.84), and Brazil (ρ=0.77-0.83) and moderate correlations with those occurring in Norway (ρ=0.32-0.35) and Finland (ρ=0.44-0.47). Similar patterns were observed in the correlation between forecasted and observed asthma hospitalizations from June 2015 to June 2016, with the number of forecasted hospitalizations differing on average between 12% (Spain) and 33% (Norway) from observed hospitalizations. Conclusions: Common cold-related web-based searches display moderate-to-strong correlations with asthma hospitalizations and may be useful in forecasting them.
• dc.format.mimetype application/pdf
• dc.identifier.citation Sousa-Pinto B, Halonen JI, Antó A, Jormanainen V, Czarlewski W, Bedbrook A, Papadopoulos NG, Freitas A, Haahtela T, Antó JM, Fonseca JA, Bousquet J. Prediction of asthma hospitalizations for the common cold using google trends: infodemiology study. J Med Internet Res. 2021;23(7):e27044. DOI: 10.2196/27044
• dc.identifier.doi http://dx.doi.org/10.2196/27044
• dc.identifier.issn 1439-4456
• dc.identifier.uri http://hdl.handle.net/10230/48316
• dc.language.iso eng
• dc.publisher JMIR Publications
• dc.relation.ispartof J Med Internet Res. 2021;23(7):e27044
• dc.rights © 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. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 06.07.2021. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri https://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Google trends
• dc.subject.keyword Asthma
• dc.subject.keyword Common cold
• dc.subject.keyword Hospitalizations
• dc.subject.keyword Mobile phone
• dc.subject.keyword Time series analysis
• dc.title Prediction of asthma hospitalizations for the common cold using google trends: infodemiology study
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion