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 1.8 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 the 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 survey.
1. A List of Prominent COVID-19 Datasets
2. Kaggle Competitions Datasets
3. Prominent COVID-19 Community Resources
4. Review of data science work related to COVID-19
For more details, refer to our paper: Leveraging Data Science To Combat COVID-19: A Comprehensive Review