Risk Model of German Corona Warning App – Reloaded

Abstract

Aim. In this paper we discuss the risk model of the German Corona Warning App in two versions. Both are based on a general semi-quantitative risk approach that is not state of the art anymore and for some application domains even deprecated. The main problem is that parameter estimates are often only ordinal scale or rank numbers for which such operations as multiplication or division are not clearly specified. Therefore, it may results in underestimation or overestimation of the associated risk. Methods. The risk models that are used in the apps are analyzed. Comparison of the nomenclature of model parameters, their influence on the result, approaches to the generation of a combined risk assessment is carried out. The effectiveness of the models is analyzed. Results. It is shown that most of the parameters in the model are used only as binary indicator variable. It has been found that the Corona Warning App uses a much more limited model that does not even assess risk, but relies on one parameter which is weighted exposure time. It has been shown that the application underestimates this parameter and therefore may erroneously reassure users. Thus, it may be concluded that the basic risk model implemented before version 1.7.1., is rather a dosimetric model that depends on the calculated virus concentration and does not depend on exposure and other parameters (excluding some threshold values). It is not even a risk model as defined by many standards. Changes of the risk model in the later version are not fundamental. In particular the later model also assesses not individual risk, but individual exposure according to the results. In addition, the model greatly underestimates the duration of exposure. Although it is reported that about 60% of the app’s users have shared positive test results, the absolute number of published results is less than 10% of all positive test results. Therefore, from an individual point of view, the application is effective only in 10% of cases, or even less. Conclusions. As the Corona Warning App also has other systematic limitations and shortcomings it is advised not to rely on its results but rather on Covid testing or vaccination. In addition, if there are enough virus tests available in the near future, the application will even become outdated. It will be better to develop an application that can assess risks a priori, as a kind of decision support for its users based on their individual risk profile.