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Pooled testing is widely used for screening for viral or bacterial infectionswith low prevalence when individual testing is not cost-efficient. Pooledtesting with qualitative assays that give binary results has been well-studied.However, characteristics of pooling with quantitative assays were mostlydemonstrated using simulations or empirical studies. We investigate propertiesof three pooling strategies with quantitative assays: traditional two-stagemini-pooling (MP) (Dorfman, 1943), mini-pooling with deconvolution algorithm(MPA) (May et al., 2010), and marker-assisted MPA (mMPA) (Liu et al., 2017).MPA and mMPA test individuals in a sequence after a positive pool and implementa deconvolution algorithm to determine when testing can cease to ascertain allindividual statuses. mMPA uses information from other available markers todetermine an optimal order for individual testings. We derive and compare thegeneral statistical properties of the three pooling methods. We show that witha proper pool size, MP, MPA, and mMPA can be more cost-efficient thanindividual testing, and mMPA is superior to MPA and MP. For diagnosticaccuracy, mMPA and MPA have higher specificity and positive predictive valuebut lower sensitivity and negative predictive value than MP and individualtesting. Included in this paper are applications to various simulations and anapplication for HIV treatment monitoring.

Informed Pooled Testing with Quantitative Assays