  In disease risk spatial analysis, many researchers especially in Indonesia
are still modelling population density as the ratio of total population to
administrative area extent. This model oversimplifies the problem, because it
covers large uninhabited areas, while the model should focus on inhabited
areas. This study uses settlement mapping against satellite imagery to focus
the model and calculate settlement area extent. As far as our search goes, we
did not find any specific studies comparing the use of settlement mapping with
administrative area to model population density in computing its correlation to
a disease case rate. This study investigates the comparison of both models
using data on Tuberculosis (TB) case rate in Central and East Java Indonesia.
Our study shows that using administrative area density the Spearman's $\rho$
was considered as "Fair" (0.566, p<0.01) and using settlement density was
"Moderately Strong" (0.673, p<0.01). The difference is significant according to
Hotelling's t test. By this result we are encouraging researchers to use
settlement mapping to improve population density modelling in disease risk
spatial analysis. Resources used by and resulting from this work are publicly
available at https://github.com/mirzaalimm/PopulationDensityVsDisease.
