  In the current study, the authors demonstrate the method aimed at analyzing
the distribution of acute coronary syndrome (ACS) cases in Saint Petersburg
using the synthetic population approach and a statistical model for arterial
hypertension prevalence. The cumulative number of emergency services calls in a
separate geographical area (a grid cell of a map) associated with ACS is
matched with the assessed number of dwellers and individuals with arterial
hypertension, which makes it possible to find locations with excessive ACS
incidence. The proposed method is implemented in Python programming language,
the visualization results are shown using QGIS open software. Three categories
of locations are proposed based on the analysis results. The demonstrated
method might be applied for using the statistical assessments of hidden health
conditions in the population to categorize spatial distributions of their
visible consequences.
