I derive two new statistics, I-pop and I-pop, that adjust Moran's I t
o study clustering of disease cases in areas (for example, counties) w
ith different, known population densities. A simulation of Lyme diseas
e in Georgia suggests that these new statistics can be more powerful t
han those currently in use. This is because they consider both spatial
pattern and non-binomial variance in rates as evidence supporting dis
ease clusters.