A Coupled Experimental and Statistical Approach for an Assessment of the Airborne Infection Risk in Event Locations

Abstract

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.