Login / Signup

Advances in using Internet searches to track dengue.

Shihao YangSamuel C KouFred Sun LuJohn S BrownsteinNicholas BrookeMauricio Santillana
Published in: PLoS computational biology (2017)
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.
Keyphrases
  • aedes aegypti
  • dengue virus
  • zika virus
  • public health
  • quality improvement
  • machine learning
  • social media
  • drinking water