Big Data, Artificial Intelligence and Epidemic Disasters. A primary Structured Literature Review

This paper presents the structured literature review of the big data and artificial intelligence in relation to the epidemic disasters among which the current SAR-COV-2. Providing a deep understanding of the state of the art, the paper drafts implications and valuable insights to manage and prevent epidemic disasters by public and private organizations drafting the research agenda. Interestingly, a two-decade study of the connection between big data, artificial intelligence and pandemic or epidemic issues is undertaken for the first time. This paper adopted a longitudinal study of the literature from the relevant databases Scopus as a leading source to get access to the articles. The diffusion of epidemic disasters among which SARS-COV-2 needs to be managed investigating several aspects such as the prevention and tracking of the epidemia or pandemia. The role of smart technologies and particularly big data and artificial intelligence is useful in tracking, preventing and managing the emergency by organizations, institutions and policymakers. This study provides for the first time the connection among big data, artificial intelligence and epidemic disasters, providing valuable implications, insights and emerging issues among which the relevance of decision-making processes and risks definition and assessment