Abstract
I derive two new statistics,IpopandI*pop, that adjust Moran'sIto study clustering of disease cases in areas (for example, counties) with different, known population densities. A simulation of Lyme disease in Georgia suggests that these new statistics can be more powerful than those currently in use. This is because they consider both spatial pattern and non‐binomial variance in rates as evidence supporting disease clusters.