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Preprint | Mathematische Entscheidungshilfe - Wie Covid-19-Tests effizienter werden könnten



Members of Die Junge Akademie show in a preprint how COVID-19 testing could become more efficient and contribute to effective control of the infection curve.


The COVID-19 pandemic affects us all: curfews, short-time work, school closures, restrictions in the scientific community etc. In the beginning, it was still possible to trace infection routes and isolate contacts at an early stage. In the meantime, only collective quarantine and protective measures can reduce infection rates. If the tracing of infection routes is no longer possible, a massive expansion of testing capacities and widespread testing of the population is the only way out of the lockdown, as this is the only way to detect and control a resurgence of infection foci at an early stage. However, given current testing capacities, it would take almost three months to test just 10% of the population in Germany - far too long for effective, lasting control and containment of the infection.

Members of Die Junge Akademie Timo de Wolff, Dirk Pflüger and Martin-Immanuel Bittner, in collaboration with Michael Rehme from the University of Stuttgart and Janin Heuer from the Technical University of Braunschweig, have published a preprint on "Evaluation of pool-based testing approaches to enable population-wide screening for COVID-19". In it, they simulate different testing methods in the USA, Germany, the UK, Italy and Singapore. With the simulation, they show that pool-based testing methods can be about eight times more efficient than single tests in current scenarios at an infection rate of 1 per cent. One tenth of the population of Germany could be tested for Covid-19 within about 10 days at such a low infection rate using realistic and optimised pool testing strategies. Pool-based testing procedures can also greatly reduce the number of false-positive diagnoses.

The interactive website can be found at https://ipvs.informatik.uni-stuttgart.de/sgs/cgi-bin/JA/covid19/.

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