Lockdown exit and control of the Covid-19 epidemic: group tests can be more effective

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

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Abstract: The lack of efficient mass testing tools for SARS-CoV-2 virus that causes Covid-19 has contributed to the accelerated spread of the epidemic. Infected people are unaware that they are spreading the disease during the incubation period as well as in asymptomatic cases or cases with mild symptoms. To limit the number of victims of the epidemic, the strategy adopted by most affected countries is therefore social distancing or complete lockdown, a strategy that can only be beneficial for a limited time, given its economic and social cost. Today, the most feasible way out of the stalemate requires widespread screening of the population. Such screening would make it possible to isolate infected people and allow others to leave the lockdown. However, production capacity for SARS-CoV-2 tests is limited. Although production is increasing, it will not allow for sufficiently systematic and frequent screening to permit the lifting of health restrictions. We here describe how the usefulness of each test can be amplified by applying it to the mixture of samples from several individuals. This technique, called group testing, has already been successfully applied on SARS-CoV-2. We show how the group-test method must be calibrated to maximize the usefulness of each available test.

Date: 2020-04
New Economics Papers: this item is included in nep-hea
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Published in 2020

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Working Paper: Lockdown exit and control of the Covid-19 epidemic: group tests can be more effective (2020)
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