本文调查了德国COVID-19感染传播的地区差异。机器学习选择程序用于从潜在影响变量池中减少变量。实证分析表明，区域结构变量和区域聚集人格特征对不同冠状病毒传播均有显著影响。后者的特点表现了联邦各州之间的心态差异。该国东北部的受影响程度较低。移民比例高的地区发病率高于其他地区。如果忽略人格特征，那么移民的影响就被高估了。在学校教育和贫困风险的影响下，进一步确定了两个重要的地区特征。教育程度低的人口比例高得不成比例的联邦州的COVID-19病例往往较少。关于贫穷，没有明确的说法。 The more the population tends to be responsible towards fellow human beings, the higher is the risk of a more pronounced spread. Where there is a tendency towards altruism, which consists of helping other people, a higher level of COVID-19 infections is revealed. A significant positive correlation between infections and testing is shown by the estimates. The link between vaccinations and the number of infections is less clear. Across the three corona waves,significant changes emerge. This relates in particular to the proportion of migrants and the proportion of families at risk of poverty. The effects decrease over the course of the pandemic.