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In the current study, the authors demonstrate the method aimed at analyzingthe distribution of acute coronary syndrome (ACS) cases in Saint Petersburgusing the synthetic population approach and a statistical model for arterialhypertension prevalence. The cumulative number of emergency services calls in aseparate geographical area (a grid cell of a map) associated with ACS ismatched with the assessed number of dwellers and individuals with arterialhypertension, which makes it possible to find locations with excessive ACSincidence. The proposed method is implemented in Python programming language,the visualization results are shown using QGIS open software. Three categoriesof locations are proposed based on the analysis results. The demonstratedmethod might be applied for using the statistical assessments of hidden healthconditions in the population to categorize spatial distributions of theirvisible consequences.

Analyzing the spatial distribution of acute coronary syndrome cases using synthesized data on arterial hypertension prevalence