Dear Colleagues,

In the recent past, several viruses, such as MPox, COVID-19, the plague, Spanish Flu, and Ebola, have rampaged unopposed across different countries, infecting and leading to the demise of people and the destruction of political regimes, affecting various sectors of the global economy, as well as causing financial and psychosocial burdens the likes of which the world has not witnessed in centuries. As a response to this, various organizations and policy-making bodies, on a global scale, have begun investigating approaches to learn from such virus outbreaks with an aim to not repeat the mistakes of the past during future virus outbreaks.

“Disease X” is a placeholder name that was adopted by the World Health Organization (WHO) in February 2018 on their shortlist of blueprint priority diseases to represent a hypothetical, unknown pathogen that could cause a future epidemic. The WHO used the placeholder term “Disease X” to make sure that its planning (such as relevant tests, expanded vaccinations, and production capabilities for vaccines) was robust, versatile, and equipped to deal with an unidentified virus. The idea of Disease X, according to Anthony Fauci (the director of the US National Institute of Allergy and Infectious Diseases at that time), was to motivate the WHO’s investigations on entire classes of viruses rather than just specific strains of certain viruses, with an aim to strengthen the WHO’s preparedness for dealing with such outbreaks. Thus, it is crucial to plan and adopt a comprehensive approach to prevent and predict a new pandemic in the future.

In the modern-day Internet of Everything era, massive volumes of user-generated material are uploaded and disseminated on the Internet. These virus outbreaks of the recent past served as “catalysts” for Internet usage which led to the generation of tremendous amounts of Big Data. This Big Data of web behavior was used as a data resource for the investigation of different research questions related to those virus outbreaks, as well as for the development of systems and applications by researchers from different disciplines, such as healthcare, epidemiology, Big Data, Data Analysis, Data Science, Machine Learning, and Natural Language Processing.

As the world prepares for Disease X, this Special Issue invites papers presenting new discoveries, innovative systems, novel applications, theoretical findings, practical solutions, use cases, analytical findings, and results based on studying, analyzing, and interpreting the Big Data on the Internet generated in the context of recent virus outbreaks, including but not limited to COVID-19, MPox, the plague, Spanish Flu, and Ebola, which have the potential to improve the global preparedness and response for Disease X.

Specific topics of interest include but are not limited to text mining, text classification, text clustering, text categorization, topic modeling, opinion mining, sentiment analysis, aspect-based sentiment analysis, spam detection, fake news tracking, misinformation detection, and the identification of conspiracy theories based on the mining and analysis of the web behavior on the Internet generated from various sources, such as social media platforms, online blogs, and websites in the context of recent virus outbreaks. 

Authors are invited to contribute their original and unpublished works. Both research and review papers are welcome. Research papers presenting preliminary and/or proof-of-concept results are also welcome. Authors may also submit extended versions of their conference papers. However, the authors of such papers should make significant improvements/extensions to their conference papers, and the details of these improvements/extensions should be clearly outlined in a cover letter accompanying the paper submission.

Dr. Nirmalya Thakur
Guest Editor

Manuscript Submission Information

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• Disease X
• COVID-19
• MPox
• web behavior
• big data
• data mining
• data analytics
• data science
• machine learning
• artificial intelligence