Dengue Fever Surveillance in India Using Text Mining in Public Media.

Despite the improvement in health conditions across the world, communicable diseases remain among the leading mortality causes in many countries. Combating communicable diseases depends on surveillance, preventive measures, outbreak investigation, and the establishment of control mechanisms. Delays in obtaining country-level data of confirmed communicable disease cases, such as dengue fever, are prompting new efforts for short- to medium-term data. News articles highlight dengue infections, and they can reveal how public health messages, expert findings, and uncertainties are communicated to the public. In this article, we analyze dengue news articles in Asian countries, with a focus in India, for each month in 2014. We investigate how the reports cluster together, and uncover how dengue cases, public health messages, and research findings are communicated in the press. Our main contributions are to 1) uncover underlying topics from news articles that discuss dengue in Asian countries in 2014; 2) construct topic evolution graphs through the year; and 3) analyze the life cycle of dengue news articles in India, then relate them to rainfall, monthly reported dengue cases, and the Breteau Index. We show that the five main topics discussed in the newspapers in Asia in 2014 correspond to 1) prevention; 2) reported dengue cases; 3) politics; 4) prevention relative to other diseases; and 5) emergency plans. We identify that rainfall has 0.92 correlation with the reported dengue cases extracted from news articles. Based on our findings, we conclude that the proposed method facilitates the effective discovery of evolutionary dengue themes and patterns.