Matematiska modeller för smittspridning av Covid -19

Abstract

The COVID -19 pandemic has for the last few years impacted all corners of the world. In many attempts to predict the development of the discrease, mathematichal modelling has been a key asset. Mathematical models are simplified descriptions of real life events an can be used both as tools to give deeper understanding about mechanisms in larger systems, and in order to make predictions about future events. This report deals with SIR models and logistic regression models to describe the hospital admissions due to COVID-19 during the first wave of the pandemic in Gothenburg. The main purpose of the project was to compare and evaluate these different models of descrease tensmission.