Operators of event locations are particularly affected by a pandemic.
Resulting restrictions may cause uneconomical business. With previous
models, only an incomplete quantitative risk assessments is possible,
whereby no suitable restrictions can be derived. Hence, a mathematical
and statistical model has been developed in order to link
measurement data of substance dispersion in rooms with epidemiological
data like incidences, reproduction numbers, vaccination rates and
test qualities. This allows a first time overall assessment of airborne
infection risks in large event locations. In these venues displacement
ventilation concepts are often implemented. In this case simplified theoretical
assumptions fail for the prediction of relevant airflows for
infection processes. Thus, with locally resolving trace gas measurements
and specific data of infection processes, individual risks can be computed
more detailed. Via inclusion of many measurement positions,
an assessment of entire event locations is possible. Embedding the
overall model in a flexible application, daily updated epidemiological
data allow latest calculations of expected new infections and individual
risks of single visitors for a certain event. With this model, an
instrument has been created that can help policymakers and operators
to take appropriate measures and to check restrictions for their effect.