title: 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.
authors.affiliation: Department of Biostatistics, Clermont University Hospital, Clermont-Ferrand, France; UMR CNRS UDA 6284 ISIT, Auvergne University, Clermont-Ferrand, France.
authors.forename: Aline
authors.initials: A
authors.lastname: Guttmann
authors.affiliation: UMR CNRS UDA 6284 ISIT, Auvergne University, Clermont-Ferrand, France.
authors.forename: Xinran
authors.initials: X
authors.lastname: Li
authors.affiliation: EA 7282 IGCNC, Auvergne University, Clermont-Ferrand, France.
authors.forename: Fabien
authors.initials: F
authors.lastname: Feschet
authors.affiliation: UMR INSERM 912 SESSTIM, Aix-Marseille University, Marseille, France.
authors.forename: Jean
authors.initials: J
authors.lastname: Gaudart
authors.affiliation: Faculty of Medicine of Grenoble FRE CNRS 3405 AGIM, J. Fourier University, La Tronche, France.
authors.forename: Jacques
authors.initials: J
authors.lastname: Demongeot
authors.affiliation: Department of Biostatistics, Clermont University Hospital, Clermont-Ferrand, France; UMR CNRS UDA 6284 ISIT, Auvergne University, Clermont-Ferrand, France.
authors.forename: Jean-Yves
authors.initials: JY
authors.lastname: Boire
authors.affiliation: Department of Biostatistics, Clermont University Hospital, Clermont-Ferrand, France; UMR CNRS UDA 6284 ISIT, Auvergne University, Clermont-Ferrand, France.
authors.forename: Lemlih
authors.initials: L
authors.lastname: Ouchchane
mesh_terms: D018376:Cardiovascular Abnormalities / Q000453:epidemiology*; D016000:Cluster Analysis; D003198:Computer Simulation; D000013:Congenital Abnormalities / Q000453:epidemiology*; D005602:France / Q000453:epidemiology; D006801:Humans; D015994:Incidence; D015233:Models, Statistical