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Group testing as a strategy for COVID-19 epidemiological monitoring and community surveillance.
Brault, Vincent; Mallein, Bastien; Rupprecht, Jean-François.
  • Brault V; Université Grenoble Alpes, CNRS, Grenoble INP, LJK, Grenoble, France.
  • Mallein B; Université Sorbonne Paris Nord, LAGA, UMR 7539, Villetaneuse, France.
  • Rupprecht JF; Aix Marseille Univ, CNRS, Centre de Physique Théorique, Turing Center for Living Systems, Marseille, France.
PLoS Comput Biol ; 17(3): e1008726, 2021 03.
Article in English | MEDLINE | ID: covidwho-1117464
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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Full text: Available Collection: International databases Database: MEDLINE Main subject: Population Surveillance / Epidemiological Monitoring / COVID-19 Testing / SARS-CoV-2 / COVID-19 / Group Processes Type of study: Diagnostic study / Observational study / Prognostic study Limits: Humans Country/Region as subject: Europa Language: English Journal: PLoS Comput Biol Journal subject: Biology / Medical Informatics Year: 2021 Document Type: Article Affiliation country: Journal.pcbi.1008726

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Population Surveillance / Epidemiological Monitoring / COVID-19 Testing / SARS-CoV-2 / COVID-19 / Group Processes Type of study: Diagnostic study / Observational study / Prognostic study Limits: Humans Country/Region as subject: Europa Language: English Journal: PLoS Comput Biol Journal subject: Biology / Medical Informatics Year: 2021 Document Type: Article Affiliation country: Journal.pcbi.1008726