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Cost analysis of coronavirus disease 2019 test strategies using pooled reverse transcriptase‐polymerase chain reaction technique
Journal of Clinical Laboratory Analysis ; 36(5), 2022.
Article in English | ProQuest Central | ID: covidwho-1842755
ABSTRACT
BackgroundThis study aimed to compare the testing strategies for COVID‐19 (i.e., individual, simple pooling, and matrix pooling) in terms of cost.MethodsWe simulated the total expenditures of each testing strategy for running 10,000 tests. Three parameters were used positive rate (PR), pool size, and test cost. We compared the total testing costs under two hypothetical scenarios in South Korea. We also simulated country‐specific circumstances in India, South Africa, South Korea, the UK, and the USA.ResultsAt extreme PRs of 0.01% and 10%, simple pooling was the most economic option and resulted in cost reductions of 98.0% (pool size ≥80) and 36.7% (pool size = 3), respectively. At moderate PRs of 0.1%, 1%, 2%, and 5%, the matrix pooling strategy was the most economic option and resulted in cost reductions of 97.0% (pool size ≥88), 86.1% (pool size = 22), 77.9% (pool size = 14), and 59.2% (pool size = 7), respectively. In both hypothetical scenarios of South Korea, simple pooling costs less than matrix pooling. However, the preferable options for achieving cost savings differed depending on each country's cost per test and PRs.ConclusionsBoth pooling strategies resulted in notable cost reductions compared with individual testing in most scenarios pertinent to real‐life situations. The appropriate type of testing strategy should be chosen by considering the PR of COVID‐19 in the community and the test cost while using an appropriate pooling size such as five specimens.
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Collection: Databases of international organizations Database: ProQuest Central Language: English Journal: Journal of Clinical Laboratory Analysis Year: 2022 Document Type: Article

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Collection: Databases of international organizations Database: ProQuest Central Language: English Journal: Journal of Clinical Laboratory Analysis Year: 2022 Document Type: Article