Aldridge, M. orcid.org/0000-0002-9347-1586 and Ellis, D. (2021) Pooled Testing and Its Applications in the COVID-19 Pandemic. In: del Carmen Boado-Penas, M., Eisenberg, J. and Şahin, S., (eds.) Pandemics: Insurance and Social Protection. Springer Actuarial . Springer, Cham , pp. 217-249. ISBN 978-3-030-78333-4
Abstract
When testing for a disease such as COVID-19, the standard method is individual testing: we take a sample from each individual and test these samples separately. An alternative is pooled testing (or ‘group testing’), where samples are mixed together in different pools, and those pooled samples are tested. When the prevalence of the disease is low and the accuracy of the test is fairly high, pooled testing strategies can be more efficient than individual testing. In this chapter, we discuss the mathematics of pooled testing and its uses during pandemics, in particular the COVID-19 pandemic. We analyse some one- and two-stage pooling strategies under perfect and imperfect tests, and consider the practical issues in the application of such protocols.
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Item Type: | Book Section |
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Copyright, Publisher and Additional Information: | © The Author(s) 2022. This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 17 Dec 2024 17:18 |
Last Modified: | 17 Dec 2024 17:18 |
Status: | Published |
Publisher: | Springer, Cham |
Series Name: | Springer Actuarial |
Identification Number: | 10.1007/978-3-030-78334-1_11 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:220826 |