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Does Online Search Behavior Coincide with Candida auris Cases? An Exploratory Study.

ABSTRACT: Candida auris is an emerging multidrug resistant infectious yeast which is challenging to eradicate and despite available laboratory methods is still difficult to identify especially in less developed countries. To limit the rapid spread of C. auris, quick and accurate detection is essential. From the perspective of disease surveillance, additional methods of tracking this yeast are needed. In order to increase global preparedness, we explored the use of online search behavior to monitor the recent global spread of C. auris. We used Google Trends to assess online search behavior on C. auris from January 2016 until August 2018. Weekly Google Trends results were counted as hits and compared to confirmed C. auris cases obtained via publications and a global expert network of key opinion leaders. A total of 44 countries generated a hit, of which 30% (13/44) were confirmed known cases, 34% (15/44) were missed known cases, 34% (15/44) were hits for unknown cases, and 2% (1/44) were confirmed unknown cases. Conclusions: Google Trends searches is rapidly able to provide information on countries with an increased search interest in C. auris. However, Google Trends search results do not generally coincide with C. auris cases or clusters. This study did show that using Google Trends provides both insight into the known and highlights the unknown, providing potential for surveillance and tracking and hence aid in taking timely precautionary measures.

SUBMITTER: Saris K

PROVIDER: S-EPMC6616941 | biostudies-literature |

REPOSITORIES: biostudies-literature

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