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Group Testing Against Covid-19

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  • Christian Gollier
  • Olivier Gossner

Abstract

It is well-known that group testing is an efficient strategy to screen for the presence of a virus. It consists in pooling n individual samples with a single test using RT-PCR. If at least one individual is infected, the test is positive, and it is negative otherwise. We show how group testing can be optimized in three applications to multiply the efficiency 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 20. The implementation of this strategy in the short run requires limited investments and could bypass the current immense shortage of testing capacity.

Suggested Citation

  • Christian Gollier & Olivier Gossner, 2020. "Group Testing Against Covid-19," EconPol Policy Brief 24, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    • Handle: RePEc:ces:econpb:_24
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    References listed on IDEAS

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    1. Thunström, Linda & Newbold, Stephen C. & Finnoff, David & Ashworth, Madison & Shogren, Jason F., 2020. "The Benefits and Costs of Using Social Distancing to Flatten the Curve for COVID-19," Journal of Benefit-Cost Analysis, Cambridge University Press, vol. 11(2), pages 179-195, July.
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    1. Jiayi Lin & Hrayer Aprahamian & George Golovko, 2024. "An optimization framework for large-scale screening under limited testing capacity with application to COVID-19," Health Care Management Science, Springer, vol. 27(2), pages 223-238, June.
    2. Sauvagnat, Julien & Barrot, Jean-Noël & Grassi, Basile, 2020. "Estimating the costs and benefits of mandated business closures in a pandemic," CEPR Discussion Papers 14757, C.E.P.R. Discussion Papers.
    3. Vincent Brault & Bastien Mallein & Jean-François Rupprecht, 2021. "Group testing as a strategy for COVID-19 epidemiological monitoring and community surveillance," PLOS Computational Biology, Public Library of Science, vol. 17(3), pages 1-25, March.
    4. Lu Tang & Yiwang Zhou & Lili Wang & Soumik Purkayastha & Leyao Zhang & Jie He & Fei Wang & Peter X.‐K. Song, 2020. "A Review of Multi‐Compartment Infectious Disease Models," International Statistical Review, International Statistical Institute, vol. 88(2), pages 462-513, August.
    5. Eslami, Keyvan & Lee, Hyunju, 2024. "Overreaction and the value of information in a pandemic," European Economic Review, Elsevier, vol. 161(C).
    6. Abel Brodeur & David Gray & Anik Islam & Suraiya Bhuiyan, 2021. "A literature review of the economics of COVID‐19," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1007-1044, September.
    7. Lipnowski, Elliot & Ravid, Doron, 2021. "Pooled testing for quarantine decisions," Journal of Economic Theory, Elsevier, vol. 198(C).
    8. Koen B. Pouwels & Laurence S. J. Roope & Adrian Barnett & David J. Hunter & Terry M. Nolan & Philip M. Clarke, 2020. "Group Testing for SARS-CoV-2: Forward to the Past?," PharmacoEconomics - Open, Springer, vol. 4(2), pages 207-210, June.
    9. Christian Gollier, 2020. "Cost–benefit analysis of age‐specific deconfinement strategies," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 22(6), pages 1746-1771, December.
    10. Nina Bobkova & Ying Chen & Hülya Eraslan, 2024. "Optimal group testing with heterogeneous risks," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 77(1), pages 413-444, February.
    11. Hanno Beck & Aloys Prinz & Elmar Wolfstetter, 2022. "Vaccination Gap, Vaccination Fraud and Inefficient Testing," Intereconomics: Review of European Economic Policy, Springer;ZBW - Leibniz Information Centre for Economics;Centre for European Policy Studies (CEPS), vol. 57(5), pages 330-336, September.
    12. C. Baunez & Mickael Degoulet & Stéphane Luchini & Patrick Pintus & Miriam Teschl, 2020. "Sub-National Allocation of COVID-19 Tests: An Efficiency Criterion with an Application to Italian Regions," Post-Print hal-03140005, HAL.
    13. Long Hai Vo & Thai‐Ha Le, 2022. "COVID‐19 test‐kit trade and trade policy: Implications for developing countries," The World Economy, Wiley Blackwell, vol. 45(10), pages 3246-3268, October.
    14. Tarun Jain & Bijendra Nath Jain, 2021. "Infection Testing at Scale: An Examination of Pooled Testing Diagnostics," Vikalpa: The Journal for Decision Makers, , vol. 46(1), pages 13-26, March.
    15. Rahul Deb & Mallesh Pai & Akhil Vohra & Rakesh Vohra, 2022. "Testing alone is insufficient," Review of Economic Design, Springer;Society for Economic Design, vol. 26(1), pages 1-21, March.
    16. Ely, Jeffrey & Galeotti, Andrea & Jann, Ole & Steiner, Jakub, 2021. "Optimal test allocation," Journal of Economic Theory, Elsevier, vol. 193(C).
    17. Karolina Drela & Agnieszka Malkowska & Anna Bera & Anna Tokarz-Kocik, 2021. "Instruments for Managing the EU Labour Market in the Face of the COVID-19 Crisis," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 984-998.

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