Multi-factorial predictive modelling of drug addiction for large urban areas

Abstract

The modelling of the society of drug addicts in order to predict the amount of drug users in the large urban areas, including age and sex structure is considered. The model parameters are estimated on the basis of the economic and psychological state of society in the specific area. The simulation framework for analysing social groups deals with the relation of drug abuse to dependence for individuals falling into certain groups. External factors of the region's development are considered as governing variables in the model. Some model results for StPetersburg (Russia) are shown. Monitoring of the drug situation is carried out using an automated information system based on Java2EE technologies and an inter-department database developed in Oracle 11g. A mathematical model for the forecasting of the drug situation is implemented using SAS/EVIL language and SAS libraries for matrix and statistical calculations.