Group testing against Covid-19

Christian Gollier () and Olivier Gossner
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Olivier Gossner: CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique

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Abstract: It is well-known that group testing is an efficient strategy to screen for the presence of a virus. It consists of pooling n individual samples with a single test using RT-PCR. If no individual in the group is infected, the group test is negative. Thus, a single test may reveal this crucial information. We show how group testing can be optimised in three applications to multiply the power of tests against Covid-19: Estimating virus prevalence to measure the evolution of the pandemic, bringing negative groups back to work to exit the current lockdown, and testing for individual infectious status to treat sick people. For an infection level around 2%, group testing could multiply the power of testing by a factor of 20. The implementation of this strategy in the short run requires limited investments and could bypass the current immense shortage of testing capacity.

Keywords: Covid-19; Testing (search for similar items in EconPapers)
Date: 2020-04-08
New Economics Papers: this item is included in nep-hea
Note: View the original document on HAL open archive server: https://hal.science/hal-02550740v1
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Citations: View citations in EconPapers (17)

Published in Covid Economics Papers, 2020, 1 (2), pp.32-42

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Working Paper: Group Testing Against Covid-19 (2020)
Working Paper: Group Testing against COVID-19 (2020)
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