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Pool testing with dilution effects and heterogeneous priors

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  • Gustavo Quinderé Saraiva

    (Business School, Pontificia Universidad Católica de Chile)

Abstract

The Dorfman pooled testing scheme is a process in which individual specimens (e.g., blood, urine, swabs, etc.) are pooled and tested together; if the merged sample tests positive for infection, then each specimen from the pool is tested individually. Through this procedure, laboratories can reduce the expected number of tests required to screen the population, as individual tests are only carried out when the pooled test detects an infection. Several different partitions of the population can be used to form the pools. In this study, we analyze the performance of ordered partitions, those in which subjects with similar probability of infection are pooled together. We derive sufficient conditions under which ordered partitions outperform other types of partitions in terms of minimizing the expected number of tests, the expected number of false negatives, and the expected number of false positive classifications. These sufficient conditions can be easily verified in practical applications once the dilution effect has been estimated. We also propose a measure of equity and present conditions under which this measure is maximized by ordered partitions.

Suggested Citation

  • Gustavo Quinderé Saraiva, 2023. "Pool testing with dilution effects and heterogeneous priors," Health Care Management Science, Springer, vol. 26(4), pages 651-672, December.
    • Handle: RePEc:kap:hcarem:v:26:y:2023:i:4:d:10.1007_s10729-023-09650-7
    DOI: 10.1007/s10729-023-09650-7
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    Cited by:

    1. Saraiva, Gustavo Quinderé, 2023. "Strategic incentives when implementing Dorfman testing with assortative matching," Economics Letters, Elsevier, vol. 232(C).

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