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Leveraging Data Science To Combat COVID-19: A Comprehensive Review

Academic Journal article by Siddique Latif, Muhammad Usman, Sanaullah Manzoor, et al, Adrian Weller

Leveraging Data Science To Combat COVID-19: A Comprehensive Review. IEEE Transactions on AI, 2020 (forthcoming)

Abstract: COVID-19, an infectious disease caused by the SARS-CoV-2 virus, was declared a pandemic by the World Health Organisation (WHO) in March 2020. At the time of writing, more than 2.8 million people have tested positive. Infections have been growing exponentially and tremendous efforts are being made to fight the disease. In this paper, we attempt to systematise ongoing data science activities in this area. As well as reviewing the rapidly growing body of recent research, we survey public datasets and repositories that can be used for further work to track COVID-19 spread and mitigation strategies. As part of this, we present a bibliometric analysis of the papers produced in this short span of time. Finally, building on these insights, we highlight common challenges and pitfalls observed across the surveyed works. We also created a live resource repository that we intend to keep updated with the latest resources including new papers and datasets.

Paper not available online at the moment (Oct 2020).