  This paper introduces a new basic risk model that could also be utilized by
Covid-19 warning apps a priori, before an action is performed. Today the common
warning apps estimate risk a posteriori and give no advice on particular
scenarios. The new model also has the advantage that the individual risks
behind the decision-making process would be uniform (in contrast to some
current regulations) and it could help to understand the risks better and could
also help to reduce risks a priori. It could be easily implemented on a single
app screen, needing only some individual preferences to be set and a handful of
adjustments to the particular scenario that shall be assessed. The disadvantage
as of any simplified semi-quantitative risk models is that calibration is not
easy (as some calibration points may even contradict) and that cumulative
effects are hard to integrate e. g. the joint effect of combined scenarios.
But, in principle calibration is feasible and it may be a good decision to
calibrate the model conservatively.
