OBJECTIVES : On January 27, 2020 the first COVID‑19 case in Germany was confirmed. By June 22, 2020, the Robert Koch-Institute (RKI) published 190,359 confirmed cases (fatal: 8,885; recovered: 175,300). Objective was to analyse if the large regional differences in the cases per 100,000 inhabitants (casesp100k, range 33.9–1,566.8) are correlated with the number of physicians per 100,000 inhabitants (physiciansp100k) and / or the gross domestic product per capita (GDPpc).

METHODS : The number of cases and fatalities per county were extracted from the official source at the RKI website. These data were supplemented by the 2019 population, the 2017 GDPpc and the 2019 physiciansp100k for each county. We used a linear regression model with physiciansp100k, GDPpc and squared GDPpc (GDPpcsq) as explanatory variables for casesp100k. For fatalities per 100,000 (fatalitiesp100k), casesp100k were the explanatory variable. Calculations were performed with statistical software R.

RESULTS : Casesp100k per county were found to be significantly decreasing with physiciansp100k (coefficient = −0.4784; p-value = 0.0172) and a significant positive, non-linear relationship with GDPpC, (coefficient = −0.0109, p-value < 0.001; GDPpcsq, coefficient < 0.0000, p-value < 0.001). This means, that 10 additional physicians translate into 4.78 additional cases and an increase of 1,000 € at the average GDP per capita of 37,158 € to 6.34 additional cases (reducing to 1.85 at 2-times the average GDP). Fatalities per 100,000, were fully explained by casesp100k as the only explanatory variable (coefficient = 1.0000; p-value < 0.001).

CONCLUSIONS : This research analysis the potential influence of socio-economic differences in German regions on COVID‑19 cases/fatalities. Due to limited data availability on the county level it was not possible to analyse potential influence factors. In interpreting of these results, it needs to be kept in mind that our analysis captures correlation between variables and does not claim a causative relationship between the variables.