Abstract
BackgroundDigital surveillance using internet search queries can improve both the sensitivity and timeliness of the detection of a health event, such as an influenza outbreak. While it has recently been estimated that the mobile search volume surpasses the desktop search volume and mobile search patterns differ from desktop search patterns, the previous digital surveillance systems did not distinguish mobile and desktop search queries. The purpose of this study was to compare the performance of mobile and desktop search queries in terms of digital influenza surveillance.Methods and ResultsThe study period was from September 6, 2010 through August 30, 2014, which consisted of four epidemiological years. Influenza-like illness (ILI) and virologic surveillance data from the Korea Centers for Disease Control and Prevention were used. A total of 210 combined queries from our previous survey work were used for this study. Mobile and desktop weekly search data were extracted from Naver, which is the largest search engine in Korea. Spearman’s correlation analysis was used to examine the correlation of the mobile and desktop data with ILI and virologic data in Korea. We also performed lag correlation analysis. We observed that the influenza surveillance performance of mobile search queries matched or exceeded that of desktop search queries over time. The mean correlation coefficients of mobile search queries and the number of queries with an r-value of ≥ 0.7 equaled or became greater than those of desktop searches over the four epidemiological years. A lag correlation analysis of up to two weeks showed similar trends.ConclusionOur study shows that mobile search queries for influenza surveillance have equaled or even become greater than desktop search queries over time. In the future development of influenza surveillance using search queries, the recognition of changing trend of mobile search data could be necessary.
Highlights
Syndromic surveillance is defined as a dynamic process of collecting near real-time data on symptom clusters that are suggestive of a biological disease outbreak [1, 2]
While it has recently been estimated that the mobile search volume surpasses the desktop search volume and mobile search patterns differ from desktop search patterns, the previous digital surveillance systems did not distinguish mobile and desktop search queries
We observed that the influenza surveillance performance of mobile search queries matched or exceeded that of desktop search queries over time
Summary
Syndromic surveillance is defined as a dynamic process of collecting near real-time data on symptom clusters that are suggestive of a biological disease outbreak [1, 2]. With international concerns about emerging infectious diseases, bioterrorism, and pandemics that threaten human or veterinary public health, the importance of syndromic surveillance systems has increased [3,4,5,6]. The 2009 H1N1 influenza pandemic highlighted the need for a syndromic surveillance system to inform policy and plan for effective health system responses [4]. Because time delays in case reporting and confirmation can interfere with the early detection of outbreaks or increases in influenza cases in the community [5], digital surveillance could improve both the sensitivity and timeliness of health event detection [5, 7]. Digital surveillance using internet search queries can improve both the sensitivity and timeliness of the detection of a health event, such as an influenza outbreak. The purpose of this study was to compare the performance of mobile and desktop search queries in terms of digital influenza surveillance
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