tetano
Editor, Senior Moderator
J Med Virol. 2020 Apr 24.
doi: 10.1002/jmv.25929. Online ahead of print.
Optimization of Group Size in Pool Testing Strategy for SARS-CoV-2: A Simple Mathematical Model
Diego Arag?n-Caqueo[SUP] 1 [/SUP], Javier Fern?ndez-Salinas[SUP] 1 [/SUP], David Laroze[SUP] 2 [/SUP]
Affiliations
Abstract
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 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 4 subjects. For a 20% prevalence, 17.9% of tests can be saved using groups of 3 subjects. For higher prevalences, the strategy flattens and loses effectiveness. Pool testing individuals for SARS-CoV-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. This article is protected by copyright. All rights reserved.
doi: 10.1002/jmv.25929. Online ahead of print.
Optimization of Group Size in Pool Testing Strategy for SARS-CoV-2: A Simple Mathematical Model
Diego Arag?n-Caqueo[SUP] 1 [/SUP], Javier Fern?ndez-Salinas[SUP] 1 [/SUP], David Laroze[SUP] 2 [/SUP]
Affiliations
- PMID: 32330297
- DOI: 10.1002/jmv.25929
Abstract
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 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 4 subjects. For a 20% prevalence, 17.9% of tests can be saved using groups of 3 subjects. For higher prevalences, the strategy flattens and loses effectiveness. Pool testing individuals for SARS-CoV-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. This article is protected by copyright. All rights reserved.