Statistical Approaches to Understand COVID-19 Severity and Fatality
- Authors: A.H. Seuc1, E. Mertens2, J.L. Peñalvo3
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View Affiliations Hide Affiliations1 National Institute of Hygiene, Epidemiology and Microbiology, Havana 10300, Cuba. 2 Institute of Tropical Medicine, 2000 Antwerp, Belgium. 3 Institute of Tropical Medicine, 2000-Antwerp, Belgium.
- Source: Moving From COVID-19 Mathematical Models to Vaccine Design: Theory, Practice and Experiences , pp 385-434
- Publication Date: September 2022
- Language: English
Statistical Approaches to Understand COVID-19 Severity and Fatality, Page 1 of 1
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Statistical methods are essential tools for confronting the current COVID-19 pandemic.These include approaches for quantifying the health impacts of the pandemic, methods for identification of patterns, or risk stratification, for estimating the risk of individuals to become infected, and of patients to die, and important clues on how to approach prediction models in a comprehensive way. The purpose of this chapter is to review basic statistical concepts related to characterization of COVID-19 severity and provide an application of a real scenario related to the identification of predictors of COVID-19 fatality in evolving databases. Some other statistical descriptions and comments are made of problems drawn from real situations.
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