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?:abstract
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Coronavirus disease (Covid-19) has reached unprecedented pandemic levels and is affecting almost every country in the world Ramping up the testing capacity of a country supposes an essential public health response to this new outbreak A pool testing strategy where multiple samples are tested in a single reverse transcriptase-polymerase chain reaction (RT-PCR) kit could potentially increase a country\'s testing capacity The aim of this study is to propose a simple mathematical model to estimate the optimum number of pooled samples according to the relative prevalence of positive tests in a particular healthcare context, assuming that if a group tests negative, no further testing is done whereas if a group tests positive, all the subjects of the group are retested individually The model predicts group sizes that range from 11 to 3 subjects For a prevalence of 10% of positive tests, 40 6% of tests can be saved using testing groups of four subjects For a 20% prevalence, 17 9% of tests can be saved using groups of three subjects For higher prevalences, the strategy flattens and loses effectiveness Pool testing individuals for severe acute respiratory syndrome coronavirus 2 is a valuable strategy that could considerably boost a country\'s testing capacity However, further studies are needed to address how large these groups can be, without losing sensitivity on the RT-PCR The strategy best works in settings with a low prevalence of positive tests It is best implemented in subgroups with low clinical suspicion The model can be adapted to specific prevalences, generating a tailored to the context implementation of the pool testing strategy
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