  Sample pooling consists in combining samples from multiple individuals into a
single pool that is then tested using a unique test-kit. A positive test means
that at least one individual within the pool is infected. Here, 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 the clinical data from
Jones et. al. (2020). 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 (e.g. nursing homes).
