Group design in group testing for COVID-19 ...
Document type :
Rapport de recherche: Autre communication scientifique (congrès sans actes - poster - séminaire...)
Title :
Group design in group testing for COVID-19 : A French case-study
Author(s) :
Almeftah, Tifaout [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Brotcorne, Luce [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Cattaruzza, Diego [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Fortz, Bernard [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Keita, Kaba [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Labbé, Martine [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Ogier, Maxime [Auteur]
Integrated Optimization with Complex Structure [INOCS]
SEMET, Frédéric [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Integrated Optimization with Complex Structure [INOCS]
Brotcorne, Luce [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Cattaruzza, Diego [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Fortz, Bernard [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Keita, Kaba [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Labbé, Martine [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Ogier, Maxime [Auteur]
Integrated Optimization with Complex Structure [INOCS]
SEMET, Frédéric [Auteur]
Integrated Optimization with Complex Structure [INOCS]
Institution :
INRIA - Centre Lille Nord Europe
Publication date :
2020-11-12
English keyword(s) :
COVID-19
Group testing
Group design
Constrained shortest path
Dynamic programming
Group testing
Group design
Constrained shortest path
Dynamic programming
HAL domain(s) :
Informatique [cs]/Recherche opérationnelle [cs.RO]
English abstract : [en]
Group testing is a screening strategy that involves dividing a population into several disjointed groups of subjects. In its simplest implementation, each group is tested with a single test in the first phase, while in the ...
Show more >Group testing is a screening strategy that involves dividing a population into several disjointed groups of subjects. In its simplest implementation, each group is tested with a single test in the first phase, while in the second phase only subjects in positive groups, if any, need to be tested again individually. In this paper, we address the problem of group testing design, which aims to determine a partition into groups of a finite population in such a way that cardinality constraints on the size of each group and a constraint on the expected total number of tests are satisfied while minimizing a linear combination of the expected number of false negative and false positive classifications. First, we show that the properties and model introduced by Aprahmian et al. can be extended to the group test design problem, which is then modeled as a constrained shortest path problem on a specific graph. We design and implement an ad hoc algorithm to solve this problem. On instances based on Santé Publique France data on Covid-19 screening tests, the results of the computational experiments are very promising.Show less >
Show more >Group testing is a screening strategy that involves dividing a population into several disjointed groups of subjects. In its simplest implementation, each group is tested with a single test in the first phase, while in the second phase only subjects in positive groups, if any, need to be tested again individually. In this paper, we address the problem of group testing design, which aims to determine a partition into groups of a finite population in such a way that cardinality constraints on the size of each group and a constraint on the expected total number of tests are satisfied while minimizing a linear combination of the expected number of false negative and false positive classifications. First, we show that the properties and model introduced by Aprahmian et al. can be extended to the group test design problem, which is then modeled as a constrained shortest path problem on a specific graph. We design and implement an ad hoc algorithm to solve this problem. On instances based on Santé Publique France data on Covid-19 screening tests, the results of the computational experiments are very promising.Show less >
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Anglais
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