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Leveraging Data Science To Combat COVID-19: A Comprehensive Review
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  • Siddique Latif ,
  • Muhammad Usman ,
  • Sanaullah Manzoor ,
  • Waleed Iqbal ,
  • Junaid Qadir ,
  • Gareth Tyson ,
  • Ignacio Castro ,
  • Adeel Razi ,
  • Maged N. Kamel Boulos ,
  • Adrian Weller ,
  • Jon Crowcroft
Siddique Latif
University of Southern Queensland, University of Southern Queensland

Corresponding Author:[email protected]

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Muhammad Usman
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Sanaullah Manzoor
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Waleed Iqbal
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Junaid Qadir
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Gareth Tyson
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Ignacio Castro
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Adeel Razi
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Maged N. Kamel Boulos
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Adrian Weller
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Jon Crowcroft
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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.
Aug 2020Published in IEEE Transactions on Artificial Intelligence volume 1 issue 1 on pages 85-103. 10.1109/TAI.2020.3020521