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Assessing the Severity of COVID-19 in the United States

In: Applications in Reliability and Statistical Computing

Author

Listed:
  • Kehan Gao

    (Eastern Connecticut State University)

  • Sarah Tasneem

    (Eastern Connecticut State University)

  • Taghi Khoshgoftaar

    (Florida Atlantic University)

Abstract

The paper proposes a unique set of relatively simple-to-construct-and-use metrics to track the spread and severity of COVID-19 cases in the United States with respect to state-wise distribution. To our knowledge, such metrics have not been proposed by others. The proposed metrics and case study presented in the paper can serve as a template for public health officials to update the disease’s severity and spread across states. Consequently, effective resources can be directed to the hard-hit states. Since the number of infections and deaths due to COVID-19 is dynamic, the proposed metrics along with the case study’s approach can be easily updated to match new available data on the disease. The primary message of our work is to provide a unique perspective into investigating the current severity and spread of the pandemic in different states in the country and highlight states with a relatively high severity score.

Suggested Citation

  • Kehan Gao & Sarah Tasneem & Taghi Khoshgoftaar, 2023. "Assessing the Severity of COVID-19 in the United States," Springer Series in Reliability Engineering, in: Hoang Pham (ed.), Applications in Reliability and Statistical Computing, pages 117-134, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-031-21232-1_6
    DOI: 10.1007/978-3-031-21232-1_6
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