Coupled dynamics of the spread of COVID-19, interventions and human behaviour

Iftekhar, Emil

dc.contributor.advisor	Priesemann, Viola Prof. Dr.
dc.contributor.author	Iftekhar, Emil
dc.date.accessioned	2024-03-14T17:24:59Z
dc.date.available	2024-03-21T00:50:09Z
dc.date.issued	2024-03-14
dc.identifier.uri	http://resolver.sub.uni-goettingen.de/purl?ediss-11858/15166
dc.identifier.uri	http://dx.doi.org/10.53846/goediss-10390
dc.format.extent	235	de
dc.language.iso	eng	de
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
dc.subject.ddc	530	de
dc.title	Coupled dynamics of the spread of COVID-19, interventions and human behaviour	de
dc.type	doctoralThesis	de
dc.contributor.referee	Priesemann, Viola Prof. Dr.
dc.date.examination	2024-02-27	de
dc.subject.gok	Physik (PPN621336750)	de
dc.description.abstracteng	The COVID-19 pandemic has presented an unprecedented challenge to global health, prompting a need for comprehensive research into the coupled dynamics of virus spread, intervention strategies, and human behavior. This dissertation provides a significant contribution to our understanding of these interconnected dynamics. We begin by establishing a theoretical framework for analyzing stability in dynamical systems. With a bedrock of theoretical understanding, the dissertation advances into the practical realm, scrutinizing the impact of the COVID-19 pandemic in Europe. An expert consultation provides projections into the future of the pandemic and identifies key dynamics and variables. Based on this knowledge we evaluate the strategies for relaxing COVID-19 restrictions in tandem with vaccination rates, emphasizing a balance between regained freedoms and the prevention of subsequent waves of infections. Moreover, we investigate the interplay between risk perception, behavior, and the spread of COVID-19, as well as the specific influence of large-scale events such as the Euro 2020 championship on viral transmission. The potential benefits and feasibility of a low-incidence strategy for managing COVID-19 are critically assessed, offering insights into optimal pandemic responses. The concluding discussions synthesize lessons learned from the pandemic, i.e. the limits of a low-incidence approach, strategic vaccination practices including the targeting of superspreaders, and the consideration of global perspectives on vaccine distribution and uptake. Thereby, the dissertation emphasizes the role of complex systems modeling in informing pandemic response.	de
dc.contributor.coReferee	Geisel, Theo Prof. Dr.
dc.subject.eng	COVID-19	de
dc.subject.eng	physics	de
dc.subject.eng	pandemic	de
dc.subject.eng	complex	de
dc.subject.eng	complex systems	de
dc.subject.eng	dynamical systems	de
dc.subject.eng	theoretical epidemiology	de
dc.subject.eng	human behaviour	de
dc.subject.eng	non-pharmaceutical interventions	de
dc.subject.eng	infectious disease modelling	de
dc.subject.eng	public health	de
dc.subject.eng	health policy	de
dc.subject.eng	mathematical modelling	de
dc.subject.eng	Bayesian Inference	de
dc.identifier.urn	urn:nbn:de:gbv:7-ediss-15166-4
dc.affiliation.institute	Fakultät für Physik	de
dc.description.embargoed	2024-03-21	de
dc.identifier.ppn	1883472067
dc.notes.confirmationsent	Confirmation sent 2024-03-14T19:45:01	de

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