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.