Since June 17th, 2020 the Corona Warn App of the German Federal Government has been available for download. After a sharp increase downloads stagnate around a total of 20 million, which is roughly one fourth of the population. Whether everyone who downloaded it actually uses it, is questionable. We want to show that the underlying concept of an app is questionable, even if each inhabitant with a smartphone downloads and uses it, it would cover barely half of each encounter where COVID-19 could actually be transmitted. We use statistical methods to show that, (i) even in the very best case with a perfectly working app the coverage would have been roughly half of all relevant encounters (ii) and that the voluntary usage of this app as well as the free decision of the infected individual to publish its (anonymized) data to warn others in fact reduces any effectiveness considerably. In addition we show that (iii) due to the design of the app there is a likely limit where the app will not be able to warn its users for mathematical and cryptographical reasons. We demonstrate by statistical means that this app could never have worked and why similar apps neither would work, let aside probably the “Trace Together” initiative of Singapore, which is based on a combination of an app plus physical tokens for those who do not own nor use smartphones. We define some requirements a successful COVID-19 tracing solution must fulfill. We show that such apps are not a solution for the problem, rather an obstacle to a real solution, because they lull their (few) users into a false sense of security which is obviously wrong, based on real figures. The paper contributes to transparency of government action during the COVID-19 pandemic. We show that other ways of contact tracing must be pursued in order to be effective and hinder the pandemic from escalating rather than providing a false feeling of safety.
|Pages (from-to)||23 - 31|
|Journal||Smart Cities and Regional Development (SCRD) Journal|
|Publication status||Published - 2021|
Austrian Classification of Fields of Science and Technology (ÖFOS)
- 102015 Information systems
- 506009 Organisation theory
- 502044 Business management