For polygon data in interval or ratio form, such as the tuberculosis incidence of different districts, Moran's I index, Geary's Ratio and the G-statistic can be used. Moran's I uses the mean of the attribute's data values as the benchmark for comparison when neighboring values are evaluated; Geary's Ratio is based on a direct comparison of neighboring values; G-statistic is based on the concept of spatial association or cross-product statistics and is capable of detecting the presence of hot spots or cold spots. In case of spatial heterogeneity, i.e. the magnitude of spatial autocorrelation varies over space, modified versions of the previous three statistics can be used to evaluate spatial association at the local scale.