Vincent Brault1, Bastien Mallein2, Jean-François Rupprecht3. 1. Université Grenoble Alpes, CNRS, Grenoble INP, LJK, Grenoble, France. 2. Université Sorbonne Paris Nord, LAGA, UMR 7539, Villetaneuse, France. 3. Aix Marseille Univ, CNRS, Centre de Physique Théorique, Turing Center for Living Systems, Marseille, France.
Abstract
We propose an analysis and applications of sample pooling to the epidemiologic monitoring of COVID-19. We first introduce a model of the RT-qPCR process used to test for the presence of virus in a sample and construct a statistical model for the viral load in a typical infected individual inspired by large-scale clinical datasets. We present an application of group testing for the prevention of epidemic outbreak in closed connected communities. We then propose a method for the measure of the prevalence in a population taking into account the increased number of false negatives associated with the group testing method.
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