[The modeling of measures of prevention and shaping proper behavior in population as tool of averting redundant risks of morbidity and mortality as exemplified by COVID-19 pandemic].

The article considers issues of how population behavior impacts realization of state anti-epidemic measures and efforts to control pandemic. Materials and Methods. The methodology of the study is based on such methods as text analysis, elastic network and construction of regression equations. The analysis of indicators characterizing state policy measures controlling pandemic was applied according to data from The Oxford COVID-19 Government Response Tracker portal. The behavioral reactions of population were assessed by text analysis of messages in Twitter and VKontakte social networks using the Rulexicon, tonalities dictionary of Russian language. The analysis of mobility was implemented on basis of data from Google Community Mobility Reports (GCMR). The study base includes data of March 12, 2020 - August 1, 2021. It is established that in controlling pandemic the most effective is to apply combination of measures implemented at state level of the Ministry of Health and the Ministry of Economic Development of the Russian Federation that permits to compensate negative effect of quarantine regimen. In the Russian Federation,effect of self-isolation measures, organization of remote work of employees of enterprises, closure of schools, wearing masks is controversial and their incorrect application can contribute to virus propagation. The vaccination measures are also effective in reducing morbidity of disease, but they are characterized by lagging effect. The approval and acceptance by population anti-epidemic measures significantly impact efficiency of pandemic control. The study results can be applied in practice of implementation of anti-epidemic measures as a tool preventing excessive risks of population morbidity and mortality.

[The social economic indices of regions and population morbidity of myocardium infarction].

In Russia, in recent decades, there were regional gapping in terms of social inequality and high level of morbidity and mortality in comparison with European countries. The high morbidity and mortality of population in the Russian Federation from diseases of circulatory system on one hand, and regional differences in terms of social economic status on the other hand, determined the purpose of the study. In order to evaluate relationship between social economic status of regions of the Russian Federation and incidence rate of myocardial infarction, the analysis was applied to standardized data of adult morbidity in classes of acute myocardial infarction and repeated myocardial infarction. Also was evaluated a number of social economic indices that reflect state and conditions of life of population. The statistical analysis was applied using MS Excel and Statistica 6 software. The critical significance level of null statistical hypothesis was established as p=0.05. When analyzing morbidity of adult population of Russia with acute and repeated myocardial infarction, significant regional differences were established. The seven factors were identified that statistically significantly affect morbidity rate of the adult population with myocardial infarction, which made it possible to divide the regions into four clusters, between which differences in morbidity rate of acute myocardial infarction were revealed. The analysis of morbidity of acute and repeated myocardial infarction established significant regional differences such as in 2017 7.7 times for acute myocardium infarction and 61 times for repeated myocardium infarction. The allocation of regional clusters depending on their social economic status allows to supplement regional and federal projects with risk-oriented technologies with purpose of decreasing morbidity of diseases of circulatory system.