A COMPARISON OF SOME SIMPLE METHODS TO IDENTIFY GEOGRAPHICAL AREAS WITH EXCESS INCIDENCE OF A RARE DISEASE SUCH AS CHILDHOOD LEUKAEMIA

Six statistics are compared in a simulation study for their ability to identify geographical areas with a known excess incidence of a rare disease. The statistics are the standardized incidence ratio, the empirical Bayes method of Clayton and Kaldor, Poisson probability, a statistic based on the &Breslow „ ’ test (BT) and two statistics based on the &Pottho!}Whittinghill ’ test (PW) for extra-Poisson variance. Two alternative processes of clustering are simulated in which high-risk locations could be caused by environmental sources or could be sites of microepidemics of an infectious agent contributing to a rare disease such as childhood leukaemia. The simulation processes use two parameters (proportion of cases found in clusters and mean cluster size) which are varied to embrace a variety of situations. Real and arti"cial data sets of small area populations are considered. The most extreme of the arti"cial sets has all areas of equal population size. The other data sets use the small census areas (municipalities) in Finland since these have extremely heterogen-eous population size distribution. Subset selection allows examination of this variability. Receiver operato