  Dengue is a mosquito-borne disease that threatens more than half of the
world's population. Despite being endemic to over 100 countries, government-led
efforts and mechanisms to timely identify and track the emergence 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, the trends in
dengue-related Google searches 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/regions: 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.
