Pool testing with dilution effects and heterogeneous priors

What is it about?

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, 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 conducted when the pooled test detects an infection. Several different partitions of the population can be used to form the pools. This study analyzes the performance of ordered partitions, those in which subjects with similar probability of infection are pooled together. It is shown that, under mild conditions, ordered partitions simultaneously minimize the expected number of tests and the expected number of false positive classifications. Under an additional technical condition regarding the dilution effect, ordered partitions also minimize the expected number of false negative classifications. Our simulations also indicate that ordered partitions tend to be more equitable, in the sense that it maximizes the minimum utility from subjects, compared to matching subjects randomly.

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Photo by National Cancer Institute on Unsplash

Photo by National Cancer Institute on Unsplash

Why is it important?

The results derived in this article can be implemented in practical settings to help policymakers and healthcare administrators design testing protocols that reduce screening costs and classification errors while ensuring equity in the testing process.

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