The results of predicting occupational injury indicators on an example of the Udmurt Republic are shown in the article. As a method of modeling the correlation-regression analysis was used. The sources of statistical information were the annual reports to the Government of the Udmurt Republic from the Ministry of Social Policy and Labor of the Udmurt Republic, data from the Federal Service of State Statistics of the Russian Federation, and from the Federal Service of State Statistics of the Udmurt Republic, forecast indicators from the program of socio-economic development of the Udmurt Republic. In modeling, the following indicators were used: average number of employees; the number of injured persons with disability for one working day or more and fatal; number of fatal injuries; the number of employees with occupational diseases; the number of days of disability in victims with disability for one working day or more and with a fatal outcome; funds spent on occupational safety activities per employee; the share of employees employed in the conditions that do not meet sanitary and hygienic standards, of the total number of employees in the studied types of the economic activities; the number of trained in occupational safety in the organizations of the Udmurt Republic; the investments in fixed assets at actual prices; gross regional product; gross regional product per capita. The quality of the obtained equations was evaluated using the coefficient of multiple determination, checking the significance of the coefficients of the linear equation of multiple regression and the significance of the linear equation as a whole. The results are the mathematical models for predicting occupational injury indicators that allow for implementing management of occupational safety in a preventive style. The results of the work are the mathematical models based on the statistics of injuries and occupational morbidity for 2002–2019 in the Udmurt Republic, designed to calculate the predicted indicators of injury rate and occupational morbidity, which showed satisfactory convergence of the obtained forecasts with actual values.
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