Article
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Analytical Parameter Estimation of the SIR Epidemic Model. Applications to the COVID-19 Pandemic.
Version 1
: Received: 26 October 2020 / Approved: 3 November 2020 / Online: 3 November 2020 (14:35:23 CET)
How to cite: Prodanov, D. Analytical Parameter Estimation of the SIR Epidemic Model. Applications to the COVID-19 Pandemic.. Preprints 2020, 2020110161 Prodanov, D. Analytical Parameter Estimation of the SIR Epidemic Model. Applications to the COVID-19 Pandemic.. Preprints 2020, 2020110161
Abstract
The dramatic outbreak of the coronavirus disease 2019 (COVID-19) pandemics and its ongoing progression boosted the scientific community's interest in epidemic modelling and forecasting. The SIR (Susceptible-Infected-Removed) model is a simple mathematical model of epidemic outbreaks, yet for decades it evaded the efforts of the community to derive explicit solution. The present work demonstrates that this is a non-trivial task. Notably, it is proven that the explicit solution of the model requires the introduction of a new transcendental special function, related to the Wright's Omega function. The present manuscript reports new analytical results and numerical routines suitable for parametric estimation of the SIR model. The manuscript introduces iterative algorithms approximating the incidence variable, which allows for estimation of the model parameters from the numbers of observed cases. The numerical approach is exemplified with data from the European Centre for Disease Prevention and Control (ECDC) for several European countries in the period Jan 2020 -- Jun 2020.
Keywords
SIR model; special functions; Lambert W function; Wright Omega function
Subject
Computer Science and Mathematics, Algebra and Number Theory
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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