A SIR-type model describing the successive waves of COVID-19

Gustavo A Muñoz-Fernández; Jesús M Seoane; Juan B Seoane-Sepúlveda

doi:10.1016/j.chaos.2021.110682

A SIR-type model describing the successive waves of COVID-19

Chaos Solitons Fractals. 2021 Mar:144:110682. doi: 10.1016/j.chaos.2021.110682. Epub 2021 Jan 14.

Authors

Gustavo A Muñoz-Fernández¹, Jesús M Seoane², Juan B Seoane-Sepúlveda¹

Affiliations

¹ Instituto de Matemática Interdisciplinar (IMI), Departamento de Análisis Matemático y Matemática Aplicada, Facultad de Ciencias Matemáticas, Universidad Complutense de Madrid, Plaza de las Ciencias 3, Madrid E-28040, Spain.
² Nonlinear Dynamics, Chaos and Complex Systems Group, Departamento de Física, Universidad Rey Juan Carlos, Tulipán s/n, Móstoles, Madrid 28933, Spain.

Abstract

It is well-known that the classical SIR model is unable to make accurate predictions on the course of illnesses such as COVID-19. In this paper, we show that the official data released by the authorities of several countries (Italy, Spain and The USA) regarding the expansion of COVID-19 are compatible with a non-autonomous SIR type model with vital dynamics and non-constant population, calibrated according to exponentially decaying infection and death rates. Using this calibration we construct a model whose outcomes for most relevant epidemiological paramenters, such as the number of active cases, cumulative deaths, daily new deaths and daily new cases (among others) fit available real data about the first and successive waves of COVID-19. In addition to this, we also provide predictions on the evolution of this pandemic in Italy and the USA in several plausible scenarios.

Keywords: COVID-19; Compartmental models; Mathematical biology; Mathematical epidemiology; Mathematical modeling.