Group testing as a strategy for COVID-19 epidemiological monitoring and community surveillance

Vincent Brault (1) , Bastien Mallein (2, 3) , Jean-François Rupprecht (4, 5)

1 SVH - Statistique pour le Vivant et l’Homme
2 LAGA - Laboratoire Analyse, Géométrie et Applications
3 DMA - Département de Mathématiques et Applications - ENS Paris
4 CPT - Centre de Physique Théorique - UMR 7332
5 CPT - E5 Physique statistique et systèmes complexes

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 then propose a method for the measure of the prevalence in a population, based on group testing, taking into account the increased number of false negatives associated with this method. Finally, we present an application of sample pooling for the prevention of epidemic outbreak in closed connected communities.

Domaines: Analyse de données, Statistiques et Probabilités [physics.data-an]; Applications [stat.AP]; Méthodologie [stat.ME]

Vincent Brault, Bastien Mallein, Jean-François Rupprecht. Group testing as a strategy for COVID-19 epidemiological monitoring and community surveillance. PLoS Computational Biology, 2021, 17 (3), pp.e1008726. ⟨10.1371/journal.pcbi.1008726⟩. ⟨hal-02868587v2⟩