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dc.contributor.authorNguyen, Ngoc T.
dc.contributor.authorAprahamian, Hrayer
dc.contributor.authorBish, Ebru K.
dc.contributor.authorBish, Douglas R.
dc.date.accessioned2019-08-12T14:13:25Z
dc.date.available2019-08-12T14:13:25Z
dc.date.issued2019-08-06
dc.identifier.citationJournal of Translational Medicine. 2019 Aug 06;17(1):252
dc.identifier.urihttp://hdl.handle.net/10919/93026
dc.description.abstractAbstract Background Pooled testing, in which biological specimens from multiple subjects are combined into a testing pool and tested via a single test, is a common testing method for both surveillance and screening activities. The sensitivity of pooled testing for various pool sizes is an essential input for surveillance and screening optimization, including testing pool design. However, clinical data on test sensitivity values for different pool sizes are limited, and do not provide a functional relationship between test sensitivity and pool size. We develop a novel methodology to accurately compute the sensitivity of pooled testing, while accounting for viral load progression and pooling dilution. We demonstrate our methodology on the nucleic acid amplification testing (NAT) technology for the human immunodeficiency virus (HIV). Methods Our methodology integrates mathematical models of viral load progression and pooling dilution to derive test sensitivity values for various pool sizes. This methodology derives the conditional test sensitivity, conditioned on the number of infected specimens in a pool, and uses the law of total probability, along with higher dimensional integrals, to derive pooled test sensitivity values. We also develop a highly accurate and easy-to-compute approximation function for pooled test sensitivity of the HIV ULTRIO Plus NAT Assay. We calibrate model parameters using published efficacy data for the HIV ULTRIO Plus NAT Assay, and clinical data on viral RNA load progression in HIV-infected patients, and use this methodology to derive and validate the sensitivity of the HIV ULTRIO Plus Assay for various pool sizes. Results We demonstrate the value of this methodology through optimal testing pool design for HIV prevalence estimation in Sub-Saharan Africa. This case study indicates that the optimal testing pool design is highly efficient, and outperforms a benchmark pool design. Conclusions The proposed methodology accounts for both viral load progression and pooling dilution, and is computationally tractable. We calibrate this model for the HIV ULTRIO Plus NAT Assay, show that it provides highly accurate sensitivity estimates for various pool sizes, and, thus, yields efficient testing pool design for HIV prevalence estimation. Our model is generic, and can be calibrated for other infections.
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleA methodology for deriving the sensitivity of pooled testing, based on viral load progression and pooling dilutionen_US
dc.typeArticle - Refereeden_US
dc.date.updated2019-08-11T03:21:11Z
dc.rights.holderThe Author(s)en
dc.contributor.departmentIndustrial and Systems Engineeringen_US
dc.title.serialJournal of Translational Medicineen_US
dc.identifier.doihttps://doi.org/10.1186/s12967-019-1992-2
dc.type.dcmitypeTexten_US


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Creative Commons Attribution 4.0 International
License: Creative Commons Attribution 4.0 International