Detecting Dengue Spread in Sri Lanka based on News Articles.



  • Nishara Kavindi
  • Peshali Randika
  • Prabashi Meddegoda


  • Mr. D.S. Deegalla


Emerging of infectious diseases such as Dengue, have become a major challenge for the world. Use of indicator-based surveillance systems is the traditional approach of monitoring diseases, which uses structured data. Use of event-based surveillance systems is the modern approach, where unstructured data such as information from the internet and social media is Used. In Sri Lanka, there are indicator-based systems established for detecting and monitoring Dengue occurrences. But it still remains a major health problem. Therefore testing and implementing the other approach to strengthen the traditional system is important. There are successful event-based systems implemented in other countries. But none of them gives detailed information about Dengue spreading in Sri Lanka. Our objective is to address this issue through an automated system which queries for newly published online news articles and classify them as Dengue-related or not, extract useful information out of Dengue-related articles about Dengue outbreaks in Sri Lanka, store them in a database and visualize through a web application. In this paper, we describe data acquisition, classification, data extraction, data storing and the visualization processes of the system.

Tags: Machine learning and Data Mining