The circular spatial scan statistic is defined through a large number of overlapping circles [18]. For each circle z, a log likelihood ratio LLR(z) is calculated, and the test statistic is defined as the maximum LLR over all circles. The scanning window will depend on the application, but it is typical to define the window as all circles centered on an observation and with a radius varying continuously from zero up to some upper limit. To ensure that both small and large clusters can be found, the upper limit is often defined so that the circle contains at most 50 percent of all observations. It is never set above that number though, since a circular cluster with high values covering for example 80 percent of all observations is more appropriatly interpreted as a spatially disconnected 'cluster' with low values covering the 20 percent of observations that are located outside the circle, since it is those 20 percent that differ from the majority of observations. The maximum cluster size can also be defined using specific units of distance (e.g., 10 km). Circles with only one observation are ignored. Let nz = ∑s∈zns be the number of observations in circle z, and let xz = ∑s∈zxs be the sum of the observed values in circle z.