Moving From COVID-19 Mathematical Models to Vaccine Design: Theory, Practice and Experiences

Statistical Approaches to Understand COVID-19 Severity and Fatality

Author(s): A.H. Seuc*, E. Mertens and J.L. Peñalvo

Pp: 385-434 (50)

DOI: 10.2174/9789815051902122010014

* (Excluding Mailing and Handling)


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.

Keywords: COVID-19, Statistics, Epidemiology, Prediction models, Health impact, Stratification, Severity, Fatality, Cuba

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