Advances in using Internet searches to track dengue
Author(s) -
Shihao Yang,
S. C. Kou,
Fred Lu,
John S. Brownstein,
Nicholas Brooke,
Mauricio Santillana
Publication year - 2017
Publication title -
plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1005607
Subject(s) - dengue fever , leverage (statistics) , the internet , government (linguistics) , disease surveillance , geography , identification (biology) , dengue vaccine , population , computer science , dengue virus , environmental health , disease , virology , medicine , biology , world wide web , artificial intelligence , botany , linguistics , philosophy , pathology
Dengue is a mosquito-borne disease that threatens over half of the world’s population. Despite being endemic to more than 100 countries, government-led efforts and tools for timely identification and tracking of new infections are still lacking in many affected areas. Multiple methodologies that leverage the use of Internet-based data sources have been proposed as a way to complement dengue surveillance efforts. Among these, dengue-related Google search trends have been shown to correlate with dengue activity. We extend a methodological framework, initially proposed and validated for flu surveillance, to produce near real-time estimates of dengue cases in five countries/states: Mexico, Brazil, Thailand, Singapore and Taiwan. Our result shows that our modeling framework can be used to improve the tracking of dengue activity in multiple locations around the world.
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