  We analyse prior risk factors for severe, critical or fatal courses of
Covid-19 based on a retrospective cohort using claims data of the AOK Bayern.
As our main methodological contribution, we avoid prior grouping and
pre-selection of candidate risk factors. Instead, fine-grained hierarchical
information from medical classification systems for diagnoses, pharmaceuticals
and procedures are used, resulting in more than 33,000 covariates. Our approach
has better predictive ability than well-specified morbidity groups but does not
need prior subject-matter knowledge. The methodology and estimated coefficients
are made available to decision makers to prioritize protective measures towards
vulnerable subpopulations and to researchers who like to adjust for a large set
of confounders in studies of individual risk factors.
