Research department: Economy and Civil Society
Project Leader within IRS: Dr. Andreas Kuebart
Project Team: Martin Stabler
Funding Organization: German Research Foundation
Duration: 02/2022 - 01/2023
Arguably unlike any other pandemic before, COVID-19 has been monitored and mapped in detail, enabling fine-grained analysis. So far, the trajectory of the COVID-19 pandemic followed a non-linear trajectory known from previous pandemics with a wave pattern implying phases of acceleration and deceleration. This research project starts from the premise, that there is unused potential in using tempo-spatial data to understand pandemic outbreaks. It aims to analyze the trajectory of the COVID-19 pandemic in Germany through a process perspective to detect spatio-temporal patterns of diffusion.
It encompasses three analytical steps. First, the development of a stage model that subdivides the pandemic trajectory in Germany in different stages by considering indicators on the national scale (e.g., spatial autocorrelation of incidence or mortality) and indicators on the regional scale (e.g., hot spots and cold spots). Second, a classification of small-scaled tempo-spatial subsets or "trajectory windows" (e.g., how the pandemic unfolded during a specific time frame in a specific region). For each stage of the pandemic, an attempt is made to identify between two and four relevant types of trajectory windows. Third, an exploration of patterns identified in the previous steps through the perspective of diffusion theory. By analyzing which types of diffusion patterns were relevant during which stage of the pandemic, the project aims to generate insights on how the geographies of spread vary over the course of the pandemic, especially considering changing conditions (e.g., new strains or infection control policies). Through this the project contributes to diffusion theory and aims to give policy recommendations regarding policies that directly address spatial diffusion (e.g., border closures).