A two-strain SARS-COV-2 model for Germany -- Evidence from a Linearization

TL;DR

This paper develops a two-strain SIR model for Germany to analyze the spread of SARS-CoV-2 variants, providing analytical insights and numerical simulations that align well with real data.

Contribution

It introduces a linearized two-strain SIR model for COVID-19 variants and derives analytical expressions for key epidemiological variables.

Findings

Analytical expressions for minimal infections and variant share dynamics.

Model predictions agree with RKI data.

Highlights impact of more infectious variants on epidemic progression.

Abstract

Currently, due to the COVID-19 pandemic the public life in most European countries stopped almost completely due to measures against the spread of the virus. Efforts to limit the number of new infections are threatened by the advent of new variants of the SARS-COV-2 virus, most prominent the B.1.1.7 strain with higher infectivity. In this article we consider a basic two-strain SIR model to explain the spread of those variants in Germany on small time scales. For a linearized version of the model we calculate relevant variables like the time of minimal infections or the dynamics of the share of variants analytically. These analytical approximations and numerical simulations are in a good agreement to data reported by the Robert Koch Institute (RKI) in Germany.