Using Machine Learning to Estimate Unobserved COVID-19 Infections in North America.

Journal: The Journal of bone and joint surgery. American volume
Published Date: Jul 1, 2020

Abstract

BACKGROUND: The detection of coronavirus disease 2019 (COVID-19) cases remains a huge challenge. As of April 22, 2020, the COVID-19 pandemic continues to take its toll, with >2.6 million confirmed infections and >183,000 deaths. Dire projections are surfacing almost every day, and policymakers worldwide are using projections for critical decisions. Given this background, we modeled unobserved infections to examine the extent to which we might be grossly underestimating COVID-19 infections in North America.

Authors

  • Shashank Vaid
    DeGroote School of Business, McMaster University, 1280 Main Street W, Hamilton, Ontario, L8S 4 M4, Canada. vaids1@mcmaster.ca.
  • Caglar Cakan
    Department of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, Germany.
  • Mohit Bhandari
    Department of Surgery, McMaster University, Hamilton, Ontario, Canada.

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