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

von Emil Iftekhar
Dissertation
Datum der mündl. Prüfung:2024-02-27
Erschienen:2024-03-14
Betreuer:Prof. Dr. Viola Priesemann
Gutachter:Prof. Dr. Viola Priesemann
Gutachter:Prof. Dr. Theo Geisel
Zum Verlinken/Zitieren: http://dx.doi.org/10.53846/goediss-10390

 

 

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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.
Keywords: COVID-19; physics; pandemic; complex; complex systems; dynamical systems; theoretical epidemiology; human behaviour; non-pharmaceutical interventions; infectious disease modelling; public health; health policy; mathematical modelling; Bayesian Inference
 
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