P1-13: Understanding scale in multi-tier networks – spatial disease dynamics and agricultural innovation

PhD student: Juliane Manitz
Thesis Committee: Prof. Thomas Kneib, Prof. Anita Schöbel
Graduation Date: 6/2014
Thesis: online publication

A key problem encountered in systems that comprise a range of temporal, spatial, or hierarchical scales is finding a systematic link between different layers of description and consolidating models that approach these systems from different angles. E.g., many contact systems have at least two angles from which statistical modelling can start:

• as phenomena driven by individual contacts and underlying social networks;
• as processes driven by populations that interact by means of interconnected networks (mobility, information flows, etc.).

In result, multiple tiers of networks moderate the individual interaction at different scales.
The goal of this project is the development of comprehensive dynamic modelling schemes that integrate these multiple tiers. Key to the successful accomplishment of these goals is a good understanding of sampling strategies in systems that interlink spatial or organisational scales. We apply these considerations to two exemplary cases, spatial disease dynamics in epidemiology, and productivity dynamics in agricultural economics, where common multi-tier structure can be found.



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