Background: To carry out mathematical modeling of key indicators of the spread of the coronavirus epidemic and, with their help, evaluate the forecast of the dynamics of its completion time. Aim: Due to a substantial request for the practice of making informed decisions to isolate the population in the face of the uncertainty of the increased risks of infection. Methods: The regression analysis was used as a method that uses the best parameter estimation of mathematical models, providing high quality dynamics of key indicators of the spread of the epidemic. To build the models, statistical data were used, which are generated by monitoring by coordinating councils to combat the spread of COVID-19 in the regions of the Russian Federation. Results: The proposed methodological apparatus allowed, based on the monitoring data of the coordinating council to combat the spread of St. Petersburg coronavirus, to carry out modeling and prediction of the course of the disease in the region. Conclusion: The proposed approach makes it possible to justifiably recommend management decisions to the administration and health authorities to create normal economic and social living conditions for residents of Russian regions, their employment, including training, during the spread of coronavirus. Recommendations: Continue to improve the apparatus for modeling and forecasting key distribution indicators of COVID-19.

The approach of modeling and forecasting of cargo turnover of transport is described. Based on statistical information on the transport activities of the Russian railway, a study of the dependence of the autocorrelation coefficients was conducted and a trend in the change in cargo turnover was established. The quality of the trend was evaluated and the point and interval forecasting of cargo turnover was carried out.

No abstract

No abstract

No abstract