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.
Advances in using Internet searches to track dengue
Shihao Yang,S. Kou,F. Lu,J. Brownstein,N. Brooke,M. Santillana
Published 2016 in PLoS Comput. Biol.
ABSTRACT
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- Publication year
2016
- Venue
PLoS Comput. Biol.
- Publication date
2016-12-08
- Fields of study
Biology, Computer Science, Mathematics, Geography, Environmental Science, Medicine
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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