Authors: Nazia Tasnim, Md. Istiak Hossain Shihab, Moqsadur Rahman, , Sheikh Rabiul Islam and Mohammad Ruhul Amin.
Dengue is one of the emergoing diseases of the century, which established itself as both endemic and epidemic particularly in the tropical and subtropical-regions. Because of it's high morbidity and mortality rates, Dengue is a significant economic and health burden for middle to lower-income countries. The lack of a stable, cost-effective, and suitable surveillance system has made the identification of dengue zones and designing potential control programs very hard. As well as, it is not possible to assess the effect of the intervention actions properly either. Therefore, most of the prevention and mitigation efforts by the associated health officials are failing. In this work, we chose Bangladesh, a developing country from the South-East Asia region with its occasional history of dengue outbreaks and with a high out-of-pocket medical expenditure, as a use case. We use some well-known data-mining techniques on the local newspapers, written in Bengali, to unearth valuable insights to develop a dengue news surveillance system. We categorize dengue-news and detect the spatio-temporal trends among crucial variables. Our technique provides an f-score of 91.45% and very closely follows the ground truth of reported cases. Besides, we identify the under-reported regions of the country effectively while establishing a meaningful relationship between complex socio-economic factors and reporting of dengue.