Previous research identifies social media as an informal source of near-real time health data that may add value to disease surveillance systems by providing broader access to health data across hard-toreach populations. This indirect health monitoring may improve public health professionals’ ability to detect disease outbreaks faster than traditional methods and to enhance outbreak response. The Philippines consists of over 7,000 islands and is prone to meteorological (storms), hydrological (floods), and geophysical disasters (earthquakes and volcanoes). In these situations, evacuation centers are used for safety and medical attention and often house up to 50K people each for 2 or more months, sometimes with unclean water sources and improper sanitation. Consequently, these conditions are a perfect venue for communicable disease transmission and have been proposed to cause disease outbreaks weeks after the original disaster occurred. Coined the social media capital of the world1, the Philippines provides a perfect opportunity to evaluate the potential of social media use in disease surveillance.
Objective
To determine the potential of Twitter data as an early warning of a likely communicable disease outbreak following a natural disaster, and if successful, develop an open-source algorithm for use by interested parties.