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Optimal retesting configurations for hierarchical group testing

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  • Michael S. Black
  • Christopher R. Bilder
  • Joshua M. Tebbs

Abstract

type="main" xml:id="rssc12097-abs-0001"> Hierarchical group testing is widely used to test individuals for diseases. This testing procedure works by first amalgamating individual specimens into groups for testing. Groups testing negatively have their members declared negative. Groups testing positively are subsequently divided into smaller subgroups and are then retested to search for positive individuals. We propose a new class of informative retesting procedures for hierarchical group testing that acknowledges heterogeneity among individuals. These procedures identify the optimal number of groups and their sizes at each testing stage to minimize the expected number of tests. We apply our proposals in two settings: human immunodeficiency virus testing programmes that currently use three-stage hierarchical testing and chlamydia and gonorrhoea screening practices that currently use individual testing. For both applications, we show that substantial savings can be realized by our new procedures.

Suggested Citation

  • Michael S. Black & Christopher R. Bilder & Joshua M. Tebbs, 2015. "Optimal retesting configurations for hierarchical group testing," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 64(4), pages 693-710, August.
    • Handle: RePEc:bla:jorssc:v:64:y:2015:i:4:p:693-710
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    File URL: http://hdl.handle.net/10.1111/rssc.2015.64.issue-4
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    Citations

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    Cited by:

    1. Hrayer Aprahamian & Douglas R. Bish & Ebru K. Bish, 2019. "Optimal Risk-Based Group Testing," Management Science, INFORMS, vol. 65(9), pages 4365-4384, September.
    2. Yaakov Malinovsky & Gregory Haber & Paul S. Albert, 2020. "An optimal design for hierarchical generalized group testing," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(3), pages 607-621, June.
    3. Christopher R. Bilder & Joshua M. Tebbs & Christopher S. McMahan, 2019. "Informative group testing for multiplex assays," Biometrics, The International Biometric Society, vol. 75(1), pages 278-288, March.
    4. Christopher S. McMahan & Joshua M. Tebbs & Timothy E. Hanson & Christopher R. Bilder, 2017. "Bayesian regression for group testing data," Biometrics, The International Biometric Society, vol. 73(4), pages 1443-1452, December.
    5. Daniel K. Sewell, 2022. "Leveraging network structure to improve pooled testing efficiency," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1648-1662, November.

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