Title: Big data, artificial intelligence and epidemic disasters. A primary structured literature review

Authors: Rosa Lombardi; Raffaele Trequattrini; Benedetta Cuozzo; Alberto Manzari

Addresses: Department of Law and Economics of Productive Activities, Sapienza University of Rome, Via del Castro Laurenziano 9, 00161 Rome, Italy ' Department of Economics and Law, University of Cassino and Southern Lazio, Via S. Angelo, Loc. Folcara, 03043, Cassino (FR), Italy ' Department of Economics and Law, University of Cassino and Southern Lazio, Via S. Angelo, Loc. Folcara, 03043, Cassino (FR), Italy ' Department of Economics, Management and Business Law, University of Bari Aldo Moro, Piazza Umberto I, 1, 70121 Bari (BA), Italy

Abstract: 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 organisations 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 organisations, 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.

Keywords: big data; artificial intelligence; epidemic disasters; SARS-COV-2; smart technologies; pandemia; decision-making process; prevention.

DOI: 10.1504/IJADS.2022.121559

International Journal of Applied Decision Sciences, 2022 Vol.15 No.2, pp.156 - 180

Received: 23 Jun 2020
Accepted: 11 Sep 2020

Published online: 11 Mar 2022 *

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