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

Aline Guttmann, Xinran Li, Fabien Feschet, Jean Gaudart, Jacques Demongeot, Jean-Yves Boire, Lemlih Ouchchane, Osman Alimamy Sankoh
2015 PLoS ONE  
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
more » ... ods 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. Fig 3. TC c of Kulldorff's spatial scan. TC c measured for four combinations of two relative risks (RR) and two annual incidences of birth defects: low RR = 3 and high RR = 6; low incidence = 0.48% births per year and high incidence = 2.26% births per year.
doi:10.1371/journal.pone.0130594 pmid:26086911 pmcid:PMC4472237 fatcat:4ei6lo5bqramxhokq3syoy4yba