Геоинформационные системы в популяционном анализе распространения депрессивных расстройств в Хабаровске

Abstract

The research is devoted to the use of modern geoinformation technologies for the analysis of spatial medical and demographic data. On the example of the medical and ecological geoinformation system (MEGIS) of Khabarovsk the possibilities of geoinformation technologies in the study of the spread of depressive disorders in a large city and the analysis of cause-and-effect relationships between this disease and some socio-economic factors are shown. The features of mathematical support of MEGIS necessary for population epidemiological analysis are considered. The possibilities of using correlation-regression and cluster-discriminant analysis for these purposes are shown. At the stage of the initial manifestation of symptoms of depression, statistically significant binary risk factors for depressive disorders were established, which were used in the diagnostic questionnaire. Developed complex recognition, classification and predictive models on the individual level, to assess the risk of developing depressive disorders and to predict the potential severity of the disease. At the population level, risk groups for depressive disorders in patients who have suffered depressive episodes in childhood should be formed. Based on the results of multi-level GIS and classification and predictive modeling based on individual clinical dynamically, socio-psychological, transcultural and environmental health risk factors formulated practical recommendations to improve the prevention of depressive disorders. The study of clinical and pathodynamic, socio-psychological, transcultural and medico-ecological aspects of non-psychotic depressive disorders with the use of geoinformation systems was carried out for the prevention of depression and mental health stabilization of the region population. The results of this research can be used by specialists in geoinformation systems, medical demography, medical psychology and social psychiatry, sociology, psychiatry, psychology and family medicine, conflictology, information modeling and system analysis in health care.