Background: Emerging infectious diseases (EIDs) are among the widespread everchanging threats to public health. Web-based queries using information gathered from social media can enhance global syndromic surveillance to trace EIDs activity. This systematic review aimed to investigate the correlation of web-based queries to outbreak of EIDs. Methods: Nine electronic databases were systematically searched and updated in August 2018 including; PubMed, Virtual Health Library (VHL), WHO Global Health Library (GHL), Scopus, ISI, Google Scholar, POPLINE, and Systems for Information of Grey Literature in Europe (SIGLE), New York Academy of Medicine (NYAM Grey Literature Report). A prior protocol was registered at Prospero (CRD42016038104). In a total five included articles, 47 datasets were included for reviewing. The correlation was assessed through Spearman and Pearson tests using either google trends or number of tweets. Results: Meta-analysis of influenza-like illness data revealed that correlation was significant (0.784 (0.743-0.820, 0.964 (0.918-0.985) for both Spearman and Pearson tests respectively. Conclusions: Web-based surveillance systems could serve as a good method in predicting events of EIDs.
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