New DFG Project: Socio-Spatial Diffusion of COVID-19 in Germany (CoDiff)
More than any other pandemic before, COVID-19 has been measured and mapped. However, the use of comparatively detailed data has not only proved to be a pillar of pandemic control, but also opens up new possibilities for research into epidemic outbreaks. It is striking that although the course of the COVID-19 pandemic corresponds to the known temporal wave pattern, these waves spread spatially in different ways. The new DFG-funded research project of the IRS “Socio-Spatial Diffusion of COVID-19 in Germany (CoDiff)” has been working on this point since the beginning of February 2022 in order to gain new insights into the spatially non-linear course of the COVID-19 pandemic. The researchers involved in the project are using the existing tempo-spatial data situation to gain new insights into the spatial spread of epidemic outbreaks.
The project comprises three analytical steps: First, a phase model will be developed that divides the course of the pandemic in Germany into different phases using indicators at the national level (e.g. spatial autocorrelation of incidence or mortality) and regional level (e.g. hot spots and cold spots). Secondly, small-scale spatio-temporal segments or “trajectory windows” (the pandemic evolution at the county or regional level during a given period) will be classified. For each phase of the pandemic, an attempt will be made to distinguish different relevant types of trajectory windows. Third, the patterns identified in the previous steps are examined from the conceptual perspective of diffusion theory.
Research Interest and Policy Recommendations
By analysing which types of diffusion patterns were relevant in which phase of the pandemic, insights will be gained into how the geographies of spread changed over the course of the pandemic in light of changing conditions (e.g. new strains or infection control measures).
Another focus of the analysis will be on the socio-spatial characteristics of the diffusion processes in order to include topological factors (i.e. the conditions at specific locations, such as nursing homes) and relational factors (i.e. the characteristics of networks of relationships). Through this perspective, the project also connects to existing work from the IRS. The CoDiff project thus aims to contribute to diffusion theory, also in order to provide recommendations for policy measures that directly target spatial diffusion (e.g. border closures).
At the IRS, the CoDiff project will involve Andreas Kuebart as project leader and Martin Stabler as researcher. The project is funded by the German Research Foundation (DFG) as part of the Foundation’s focused funding of COVID-19-related research. The first results of the project, which started in February 2022, are expected as early as summer 2022.