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Assessing Epidemic Diseases and Public Opinion through Popular Search Behavior Using Non-English Language Google Trends (Preprint)


 BACKGROUND
 Web social media has identified to utilize as an epidemic outbreaks surveillance tool. However, the correlation between non-English language queries search data and epidemic diseases remains unclear.
 
 
 OBJECTIVE
 This study aimed to confirm the suitable non-English language keywords research relative intensities that were sensitive and specific to estimate the level of epidemic disease and the public opinion in non-English language country. Moreover, our approach indicated that a surveillance system based on Internet activity can be served an essential tool for detecting emerging diseases with distinct symptoms (e.g. zika virus fever in Brazil, 2015), and estimating the local epidemic diseases (e.g. enterovirus infectious disease in Taiwan, 2012). Otherwise, we further evaluated whether the social media reflected social uneasiness and fear during epidemic outbreaks and natural catastrophes. Our specific aim is to develop a suitable surveillance system for monitoring epidemic outbreak and observing related public opinion in the non-English language countries.
 
 
 METHODS
 The present study was based on freely available weekly epidemic incidence data from Taiwan Center for Disease Control, and the web search query data obtained from Google Trends between October 4, 2015, and April 2, 2016. To validate whether the non-English query keywords were the excellent surveillance tools, we estimated the correlation between the web query data and epidemic incidence in Taiwan.
 
 
 RESULTS
 Based on our approach, the total of 8 influenza-related queries was introduced to the analysis. The keywords, “感冒(common cold), 發燒(fever), and 咳嗽(cough)”, revealed good to excellent correlation between the Google Trends query data and influenza incidence (r= 0.89, P< 0.001; r= 0.77, p< 0.001; r= 0.79, p< 0.001, respectively). Moreover, those also displayed a high correlation with the influenza-like illness emergency and outpatient visits. We further found the query ”腸病毒 (enteroviruses)” in Google Trends, which showed excellent correlation with enterovirus infected patients in the emergency department (r= 0.91, p< 0.001).
 
 
 CONCLUSIONS
 This result suggested that Google Trends can serve as a good surveillance tool for epidemic outbreaks even in non-English language countries. Due to online search activity indicated people’s concerns for epidemic diseases even when they do not visit hospitals, it prompted us to develop the effectiveness of epidemic monitoring in web social media, which reflected the infectious trend more timeliness than traditional reporting system. In addition, the web queries data in suitable non-English search terms can provide more advantage information for medical education, healthcare, and disease prevention.
