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Simple Formulae, Deep Learning and Elaborate Modelling for the COVID-19 Pandemic

Published version
Peer-reviewed

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Authors

Fokas, Athanassios S 
Tsiodras, Sotirios 

Abstract

jats:pPredictive modelling of infectious diseases is very important in planning public health policies, particularly during outbreaks. This work reviews the forecasting and mechanistic models published earlier. It is emphasized that researchers’ forecasting models exhibit, for large t, algebraic behavior, as opposed to the exponential behavior of the classical logistic-type models used usually in epidemics. Remarkably, a newly introduced mechanistic model also exhibits, for large t, algebraic behavior in contrast to the usual Susceptible-Exposed-Infectious-Removed (SEIR) models, which exhibit exponential behavior. The unexpected success of researchers’ simple forecasting models provides a strong support for the validity of this novel mechanistic model. It is also shown that the mathematical tools used for the analysis of the first wave may also be useful for the analysis of subsequent waves of the COVID-19 pandemic.</jats:p>

Description

Keywords

50 Philosophy and Religious Studies, 5002 History and Philosophy Of Specific Fields, 3 Good Health and Well Being

Journal Title

Encyclopedia

Conference Name

Journal ISSN

2673-8392
2673-8392

Volume Title

2

Publisher

MDPI AG