From May to July 2015, there was a nation-wide outbreak of Middle East respiratory syndrome (MERS) in Korea. MERS is caused by MERS-CoV, an enveloped, positive-sense, single-stranded RNA virus belonging to the family Coronaviridae. Despite expert opinions that the danger of MERS might be exaggerated, there was an overreaction by the public according to the Korean mass media, which led to a noticeable reduction in social and economic activities during the outbreak. To explain this phenomenon, we presumed that machine learning-based analysis of media outlets would be helpful and collected a number of Korean mass media articles and short-text comments produced during the 10-week outbreak. To process and analyze the collected data (over 86 million words in total) effectively, we created a methodology composed of machine-learning and information-theoretic approaches. Our proposal included techniques for extracting emotions from emoticons and Internet slang, which allowed us to significantly (approximately 73%) increase the number of emotion-bearing texts needed for robust sentiment analysis of social media. As a result, we discovered a plausible explanation for the public overreaction to MERS in terms of the interplay between the disease, mass media, and public emotions.

The use of legislation as a health protection tool forms an important and distinct aspect in the arena of public health. A review of Hong Kong's infectious disease legislation was conducted with a view to updating the legal framework for the prevention of infectious diseases, in order to strengthen the capacity of law to support strategy in the control of infectious diseases. This article shares Hong Kong's experience in reforming its public health legislation to: (1) update terminology and re-organize provisions in accordance with modern public health disease control principles and control mechanisms for disease; (2) enhance responsiveness for better preparedness and flexibility in handling emergent infections; (3) ensure appropriate checks and balances to coercive powers; and (4) introduce emergency powers for the handling of public health emergencies.

The Internet encompasses websites, email, social media, and Internet-based television. Given the widespread use of networked computers and mobile devices, it has become possible to monitor the behavior of Internet users by examining their access logs and queries. Based on large-scale web and text mining of Internet media articles and associated user comments, we propose a framework to rapidly monitor how the emotion of the public changes over time and apply the framework to a real case of an infectious disease. The proposed methodology will be helpful for performing cost-effective and time-efficient public health monitoring that otherwise would take orders-of-magnitude more time and resources if traditional epidemiology techniques were used.

Mycobacterium avium subsp. paratuberculosis (MAP) is the causative agent of Johne’s disease (JD), and it causes diarrhea and weakness in cattle. During a long subclinical stage, infected animals without clinical signs shed pathogens through feces. For this reason, the diagnosis of JD during the subclinical stage is very important. Circulating miRNAs are attracting attention as useful biomarkers in various veterinary diseases because of their expression changes depending on the state of the disease. Based on current knowledge, circulating miRNAs extracted from bovine serum were used to develop a diagnostic tool for JD. In this study, the animals were divided into 4 groups according to fecal shedding, the presence of antibodies, and clinical signs. Gene expression was analyzed by performing miRNA sequencing for each group, and it was identified that the miRNA expression changed more as the MAP infection progressed. The eight miRNAs that were differentially expressed in all infected groups were selected as biomarker candidates based on their significant differences compared to the control group. These biomarker candidates were validated by qRT-PCR. Considering the sequencing data, two upregulated miRNAs and two downregulated miRNAs showed the same trend in the validation results. Network analysis was also conducted and the results showed that mRNAs (IL-10, TGF-β1) associated with regulatory T cells were predicted to be activated in the subclinical stage. Taken together, our data suggest that two miRNAs (bta-miR-374b, bta-miR-2887) may play major roles in the immune response to MAP infection during the subclinical stage.