COVID-19: Heat Map of Local 7-day Incidences over Time
The map shows the local 7-day-incidence rate of the officially reported Covid-19 infections in Germany over time. The calculation is based on the official data from Robert-Roch-Institute (RKI), which are freely available online. The data is available on a daily basis at the district level. The map results from the master thesis of Lukas Fuchs in the Joint Master Studiengang Statistics, in cooperation with Prof. Dr. Ulrich Rendtel (Department of Economics, Freie Universität Berlin) and INWT Statistics. An advanced algorithm is used to plot national-wide infection cases, revealing more visible patterns and providing at least 30% higher accuracy compared to district-level incidence data. We update the map daily when new data is available from the RKI. The data is loaded automatically and the model is applied for the last 7 days. It can happen that we do not get current data from certain regions in Germany for more than 7 days. In case this happens you see a local incidence of 0 there.
Note: The map is only available for current browsers (Firefox, Chrome, Safari, Edge).
The illustration displays the estimated local 7-day-incident figures. In contrast to the false assumption of the constant incidence rate per district as most suggests, the missing precise location of infection is estimated by a statistical algorithm. Based on the simulated positions of the infections, a new map of the incidences is generated. This is used again to determine the exact positions of the infection cases in the district. The process will iterate until there are no more changes. The application of this Simulated Expectation Maximization (SEM) Algorithm for the construction of Intensity Map (heat map) is described by Gross et al. The raw data for the districts (7 day case count) originates from the Robert- Koch-Institute and can be downloaded here.
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Groß, M.; Kreutzmann, A.-K.; Rendtel, U.; Schmid, T.; Tzavidis, N. (2020): Switching between different area systems via simulated geo-coordinates: A case study for student residents in Berlin. Journal of Official Statistics, 36, 297-314, http://dx.doi.org/10.2478/JOS-2020-0016