While standard methods for reporting disease burden typically only adjust for age and sex in each area, spatial smoothing also incorporates the geographical structure of the data. It does this by ‘borrowing’ data from the neighbouring geographical areas.
This provides greater stability for the estimates and greatly reduces any risk of individuals being identified.
These protective effects of spatial smoothing are most pronounced for areas where it is needed the most, that is, those with the smallest numbers of cases. Smoothed estimates are designed to reflect the real differences in the underlying rate or risk between areas. See spatial smoothing tour.
