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

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. By mid-August 2020, more than 21 million people have tested positive worldwide. Infections have been growing rapidly and tremendous efforts are being made to fight the disease. In this paper, we attempt to systematise the various COVID-19 research activities leveraging data science, where we define data science broadly to encompass the various methods and tools—including those from artificial intelligence (AI), machine learning (ML), statistics, modeling, simulation, and data visualization—that can be used to store, process, and extract insights from data. In addition to 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 at https://github.com/Data-Science-and-COVID-19/Leveraging-Data-Science-To-Combat-COVID-19-A-Comprehensive-Review that we intend to keep updated with the latest resources including new papers and datasets. Impact Statement—Data science, defined broadly, will play a central role in the global response to the COVID-19 pandemic. This paper facilitates the rapid engagement of data science and AI researchers with the breadth of the ongoing research work. In particular, we identify the major challenges involved, promising directions for further work, and important community resources. Given the interdisciplinary nature of the challenge, this review will help data scientists form collaborations across disciplines. We also elaborate the benefits of data science to strategists and policymakers and guide them in coming to grips with the challenges, opportunities, and pitfalls involved in using data science to combat the COVID-19 pandemic.