Real-Time Estimation of R 0 for COVID-19 Spread

Theodore E. Simos, Charalampos Tsitouras, Vladislav N. Kovalnogov, Ruslan V. Fedorov and Dmitry A. Generalov
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Theodore E. Simos: Laboratory of Applied Mathematics for Solving Interdisciplinary Problems of Energy Production, Ulyanovsk State Technical University, Severny Venetz St. 32, 432027 Ulyanovsk, Russia
Charalampos Tsitouras: General Department, Euripus Campus, National and Kapodistrian University of Athens, 34400 Athens, Greece
Vladislav N. Kovalnogov: Laboratory of Applied Mathematics for Solving Interdisciplinary Problems of Energy Production, Ulyanovsk State Technical University, Severny Venetz St. 32, 432027 Ulyanovsk, Russia
Ruslan V. Fedorov: Laboratory of Applied Mathematics for Solving Interdisciplinary Problems of Energy Production, Ulyanovsk State Technical University, Severny Venetz St. 32, 432027 Ulyanovsk, Russia
Dmitry A. Generalov: Laboratory of Applied Mathematics for Solving Interdisciplinary Problems of Energy Production, Ulyanovsk State Technical University, Severny Venetz St. 32, 432027 Ulyanovsk, Russia

Mathematics, 2021, vol. 9, issue 6, 1-9

Abstract: We propose a real-time approximation of R 0 in an SIR-type model that applies to the COVID-19 epidemic outbreak. A very useful direct formula expressing R 0 is found. Then, various type of models are considered, namely, finite differences, cubic splines, Piecewise Cubic Hermite interpolation and linear least squares approximation. Preserving the monotonicity of the formula under consideration proves to be of crucial importance. This latter property is preferred over accuracy, since it maintains positive R 0 . Only the Linear Least Squares technique guarantees this, and is finally proposed here. Tests on real COVID-19 data confirm the usefulness of our approach.

Keywords: SIR epidemic model; COVID-19; ordinary differential equations; splines; least squares (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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