COVID-19 Screening: A New Model for Assessing the Efficiency of Group Testing

Pooling in a school/university setting: saliva or nose samples from students sha
Pooling in a school/university setting: saliva or nose samples from students sharing the same classroom/student residence are pooled in a single tube; the virological status of the mixture is assessed by a single molecular test (RT-qPCR or RT-LAMP). A positive test indicates that at least one individual is infected with CoV2-SARS, allowing early action to be taken to contain an outbreak. The screening process can be repeated on a regular basis. © Jean-François Rupprecht, the Centre for Theoretical Physics (CNRS/Aix-Marseille Université/Université de Toulon).
Pooling in a school/university setting: saliva or nose samples from students sharing the same classroom/student residence are pooled in a single tube; the virological status of the mixture is assessed by a single molecular test (RT-qPCR or RT-LAMP). A positive test indicates that at least one individual is infected with CoV2-SARS, allowing early action to be taken to contain an outbreak. The screening process can be repeated on a regular basis. Jean-François Rupprecht, the Centre for Theoretical Physics (CNRS/Aix-Marseille Université/Université de Toulon). How best to evaluate the performance of a group testing strategy for the SARS-CoV-2 virus, which involves pooling samples from multiple individuals in order to conduct a single RT-PCR test on the whole group? To do precisely that, scientists from the CNRS, l'université Grenoble Alpes, and l'université Sorbonne Paris Nord 1 have developed a model that evaluates the efficiency of such tests. Their theoretical study accounts for both dilution effect and the detection limits of the RT-PCR test, in an effort to assess the number of potential false negatives based on pooled sample size, to optimize group size thereby minimizing epidemic risk, and finally to more accurately determine the number of contaminated individuals within a given population. It was published on March 4, 2021 in PLOS Computational Biology.
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