Cluster Detection Tests in Spatial Epidemiology: A Global Indicator for Performance Assessment

Abstract : In cluster detection of disease, the use of local cluster detection tests (CDTs) is current. These methods aim both at locating likely clusters and testing for their statistical significance. New or improved CDTs are regularly proposed to epidemiologists and must be subjected to performance assessment. Because location accuracy has to be considered, performance assessment goes beyond the raw estimation of type I or II errors. As no consensus exists for performance evaluations, heterogeneous methods are used, and therefore studies are rarely comparable. A global indicator of performance, which assesses both spatial accuracy and usual power, would facilitate the exploration of CDTs behaviour and help between-studies comparisons. The Tanimoto coefficient (TC) is a well-known measure of similarity that can assess location accuracy but only for one detected cluster. In a simulation study, performance is measured for many tests. From the TC, we here propose two statistics, the averaged TC and the cumulated TC, as indicators able to provide a global overview of CDTs performance for both usual power and location accuracy. We evidence the properties of these two indicators and the superiority of the cumulated TC to assess performance. We tested these indicators to conduct a systematic spatial assessment displayed through performance maps.
Type de document :
Article dans une revue
PLoS ONE, Public Library of Science, 2015, 〈10.1371/journal.pone.0130594.g009〉
Liste complète des métadonnées

Littérature citée [27 références]  Voir  Masquer  Télécharger

https://hal-amu.archives-ouvertes.fr/hal-01202624
Contributeur : Administrateur Hal Amu <>
Soumis le : lundi 21 septembre 2015 - 14:37:52
Dernière modification le : mardi 5 décembre 2017 - 16:16:04
Document(s) archivé(s) le : mardi 29 décembre 2015 - 08:59:20

Fichier

fetchObject.pdf
Fichiers éditeurs autorisés sur une archive ouverte

Identifiants

Collections

Citation

Aline Guttmann, Xinran Li, Fabien Feschet, Jean Gaudart, Jacques Demongeot, et al.. Cluster Detection Tests in Spatial Epidemiology: A Global Indicator for Performance Assessment. PLoS ONE, Public Library of Science, 2015, 〈10.1371/journal.pone.0130594.g009〉. 〈hal-01202624〉

Partager

Métriques

Consultations de la notice

344

Téléchargements de fichiers

67