Piecewise SEIUR model for the spread of COVID-19

Abstract

Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that can be transmitted through human interaction. In this thesis, we present a Piecewise Susceptible-Exposed-Infectious-Unreported-Removed model (SEIUR) for infectious diseases and discuss it qualitatively and quantitatively. The parameters are explored by mathematical and statistical methods. Numerical simulations of these models are performed on COVID-19 US data, and Python is used in the visualization of the simulation results. Outbreak factor is generated by piecewise SEIUR model to explore the future trend of the US pandemic. Several error metrics are given to discuss the accuracy of these models. The main achievement of this thesis is to propose the SEIUR model and piecewise SEIUR model and to find the relationship between the spread of the pandemic and control strategies by observing the results of the numerical simulations. Performance analysis of SEIUR model and piecewise SEIUR model is presented based on COVID-19 data.