Matematiska modeller för smittspridning av Covid -19

dc.contributor.author	Johansson, Dan
dc.contributor.author	Kulagic, Erman
dc.contributor.author	Nilsen, William
dc.contributor.author	Olofsson, Zackarias
dc.contributor.author	Simonsson, Isabella
dc.contributor.department	Chalmers tekniska högskola / Institutionen för matematiska vetenskaper	sv
dc.contributor.examiner	Dinger, Ulla
dc.contributor.supervisor	Gerlee, Philip
dc.date.accessioned	2022-07-04T12:03:24Z
dc.date.available	2022-07-04T12:03:24Z
dc.date.issued	2022	sv
dc.date.submitted	2020
dc.description.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.	sv
dc.identifier.coursecode	MVEX01	sv
dc.identifier.uri	https://hdl.handle.net/20.500.12380/305035
dc.language.iso	swe	sv
dc.setspec.uppsok	PhysicsChemistryMaths
dc.title	Matematiska modeller för smittspridning av Covid -19	sv
dc.type.degree	Examensarbete för kandidatexamen	sv
dc.type.uppsok	M2

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Namn:: MVEX01-22-07-Matematiska modeller för smittspridning av Covid -19.pdf
Storlek:: 1.52 MB
Format:: Adobe Portable Document Format
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