05/12/2020 | Universität Stuttgart | News

How Covid-19 Testing Can Become More Efficient

Mathematical Decision Support that calculates which method is most effective in identifying all Covid-19 patients in a positive sample pool

With the help of so-called pooling procedures, samples from different people can be combined into a pool and tested for Covid-19 collectively in a single test kit. An interdisciplinary team of mathematicians, computer scientists and medical doctors from the Junge Akademie, the Technische Universität Braunschweig, the Universität Stuttgart and the company Arctoris has developed a decision support tool that calculates which method is most effective in identifying all Covid-19 patients in a positive sample pool. Their simulations show that in Germany, pool-based test methods can be about eight times more efficient than individual tests at a low infection rate. The team recently published the results in a preprint on "arXiv" and as a website.

Beim Proben-Pooling wird das Probenmaterial von unterschiedlichen Personen zu einer Probe (Pool) zusammengefügt und gemeinsam getestet. Das kann bei einer niedrigen Infektionsrate im Vergleich zum individuellen Testen Zeit und Testkapazitäten sparen. Fällt die Probe negativ aus, muss keine der enthaltenen Einzelproben gesondert überprüft werden. Bei einem positiven Ergebnis werden weitere Tests durchgeführt. Dafür eignen sich je nach Szenario unterschiedliche Verfahren.

There are different methods to diversify the pool of samples in case of a positive result: For example, all samples could be reexamined individually (2-level pooling). It would also be possible to split the pool and test both halves. If the result is positive, the samples would be divided and tested again (binary splitting).

photo: Timo de Wolff/TU Braunschweig

Further information


Technische Universität Braunschweig
Prof. Dr. Timo de Wolff
Institute for Analysis and Algebra
Universitätsplatz 2
38106 Braunschweig
Tel. +49 (0) 531 391-7503

Universität Stuttgart
Prof. Dr. Dirk Pflüger
Institut of Parallel and Distributed Systems
Universitätsstr. 38
70569 Stuttgart
Tel. +49 (0) 711 685-88447

Arctoris Ltd
Dr. Dr. Martin-Immanuel Bittner
9400 Garsington Road
Oxford OX4 2HN
Vereinigtes Königreich
Tel. +44 (0) 7713 828 576

De Wolff, Timo; Pflüger, Dirk; Rehme, Michael; Heuer, Janin; Bittner, Martin-Immanuel: Evaluation of Pool-based Testing Approaches to Enable Population-wide Screening for COVID-19 (arXiv:2004.11851)