JDS Journal of Data Science 1683-8602 1680-743X 1680-743X School of Statistics, Renmin University of China JDS993 10.6339/21-JDS993 Data Science in Action Testing for COVID-19: Some Statistical Issues YiGrace Y.gyi5@uwo.ca12∗ HeWenqing1 LinDennis K. J.3 YuChun Ming4 Department of Statistical and Actuarial Sciences, University of Western Ontario, London, Ontario, Canada Department of Computer Science, University of Western Ontario, London, Ontario, Canada Department of Statistics, Pennsylvania State University, University Part, PA, USA Northfield FHO @ Boardwalk Medical Center, Waterloo, Ontario, Canada Corresponding author. Email: gyi5@uwo.ca. 2021752021192243252 Supplementary Material

The Diamond Princess data and the R code for the figures in the paper are available online at the Journal of Data Science website.

 162020 192020 2021 The Author(s). Published by the School of Statistics and the Center for Applied Statistics, Renmin University of China.2021 Open access article under the CC BY license.

The swift spread of the novel coronavirus is largely attributed to its stealthy transmissions in which infected patients may be asymptomatic or exhibit only flu-like symptoms in the early stage. Undetected transmissions present a remarkable challenge for the containment of the virus and pose an appalling threat to the public. An urgent question is on testing of the coronavirus. In this paper, we evaluate the situation from the statistical viewpoint by discussing the accuracy of test procedures and stress the importance of rationally interpreting test results.

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