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Article Abstract
Background: An increase in online searches on health topics may either mirror epidemiological changes or reflect media coverage. In the context of COVID-19, this is particularly relevant, as COVID-19 symptoms may be mistaken for those of respiratory disease exacerbations. Therefore, we aimed to assess Internet search patterns on asthma and chronic obstructive pulmonary disease (COPD) in the context of COVID-19, as compared to searches on other chronic diseases.
Methods: We retrieved Google Trends (GTs) data on two respiratory (asthma and COPD) and three non-respiratory (diabetes, hypertension, and Crohn's disease) chronic diseases over the past 5 years (up to May 31, 2020). For 54 countries, and for each disease, we built autoregressive integrated moving average (ARIMA) models to predict GTs for 2020 based on 2015-2019 search patterns. In addition, we estimated the proportion of searches in which COVID-19-related terms were used. To assess the potential impact of media coverage on online searches, we assessed whether weekly "asthma" GTs correlated with the number of Google News items on asthma.
Results: Over the past 5 years, worldwide search volumes for asthma and COPD reached their maximum values in March 2020. Such was not observed for diabetes, hypertension and Crohn's disease. In 38 (70%) countries, GTs on asthma were higher in March 2020 than the respective maximum predicted values. This compares to 19 countries for COPD, 23 for hypertension, 11 for Crohn's disease, and 9 for diabetes. Queries with COVID-19-related terms represented up to 47.8% of the monthly searches on asthma, and up to 21.3% of COPD searches. In most of the assessed countries, moderate-strong correlations were observed between "asthma" GTs and the number of news items on asthma.
Conclusions: During March 2020, there was a peak in searches on asthma and COPD, which was probably mostly driven by media coverage, as suggested by their simultaneity in several countries with different epidemiological situations.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7604916 | PMC |
| http://dx.doi.org/10.1186/s13601-020-00352-9 | DOI Listing |
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