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Informative group testing for multiplex assays

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  • Christopher R. Bilder
  • Joshua M. Tebbs
  • Christopher S. McMahan

Abstract

Infectious disease testing frequently takes advantage of two tools—group testing and multiplex assays—to make testing timely and cost effective. Until the work of Tebbs et al. (2013) and Hou et al. (2017), there was no research available to understand how best to apply these tools simultaneously. This recent work focused on applications where each individual is considered to be identical in terms of the probability of disease. However, risk‐factor information, such as past behavior and presence of symptoms, is very often available on each individual to allow one to estimate individual‐specific probabilities. The purpose of our paper is to propose the first group testing algorithms for multiplex assays that take advantage of individual risk‐factor information as expressed by these probabilities. We show that our methods significantly reduce the number of tests required while preserving accuracy. Throughout this paper, we focus on applying our methods with the Aptima Combo 2 Assay that is used worldwide for chlamydia and gonorrhea screening.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:biomet:v:75:y:2019:i:1:p:278-288
    DOI: 10.1111/biom.12988
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    File URL: https://doi.org/10.1111/biom.12988
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    References listed on IDEAS

    as
    1. Joshua M. Tebbs & Christopher S. McMahan & Christopher R. Bilder, 2013. "Two-Stage Hierarchical Group Testing for Multiple Infections with Application to the Infertility Prevention Project," Biometrics, The International Biometric Society, vol. 69(4), pages 1064-1073, December.
    2. 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.
    3. Michael S. Black & Christopher R. Bilder & Joshua M. Tebbs, 2012. "Group testing in heterogeneous populations by using halving algorithms," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 61(2), pages 277-290, March.
    4. Peijie Hou & Joshua M. Tebbs & Christopher R. Bilder & Christopher S. McMahan, 2017. "Hierarchical group testing for multiple infections," Biometrics, The International Biometric Society, vol. 73(2), pages 656-665, June.
    5. Christopher S. McMahan & Joshua M. Tebbs & Christopher R. Bilder, 2012. "Informative Dorfman Screening," Biometrics, The International Biometric Society, vol. 68(1), pages 287-296, March.
    6. Bilder, Christopher R. & Tebbs, Joshua M. & Chen, Peng, 2010. "Informative Retesting," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 942-955.
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    Cited by:

    1. Wei Zhang & Aiyi Liu & Qizhai Li & Paul S. Albert, 2020. "Nonparametric estimation of distributions and diagnostic accuracy based on group‐tested results with differential misclassification," Biometrics, The International Biometric Society, vol. 76(4), pages 1147-1156, December.

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