Abstract: COVID-19, an infectious disease caused by the SARS-CoV-2 virus, was declared a pandemic by the World Health Organization (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, the authors attempt to systematize the various COVID-19 research activities leveraging data science, from 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, the authors survey public datasets and repositories that can be used for further work to track COVID-19 spread and mitigation strategies for authenticity and comparison purposes. As part of this, they present a bibliometric analysis of the papers produced in this short span of time. Finally, building on these insights, they highlight common challenges and pitfalls observed across the surveyed works.
Keywords: Coronavirus, COVID-19, Data Science, Data Visualization, Modeling, Pandemic, Simulation, Statistics
| DOI: 10.17148/IJARCCE.2021.10334