Statistic and dynamic aspects of the prediction of the COVID-19 spread in Nizhny Novgorod region
The aim of the study was to develop models to predict a range of possible scenarios for spreading the COVID-19 in the Nizhny Novgorod region. Materials and methods. The statistical open data web sites were used for building models. The dynamic model was calculated using computer simulation in the MatLab R2018b application package. In statistical models’ building MS Excel was used, as well as the AtteStat application package was used for statistical processing of time series. As the main variables of the model, publicly available values were chosen: the number of infected patients, the number of deaths and the number of recovered patients. The values of changes of these characteristics were described using mathematical and statistical methods. Results. Mathematical and statistical analysis of the evolution of the main indicators of the epidemic over time showed the distinctive features of the models. The dynamical model allows us to estimate the rate of growth and fall of the number of infected in the study population. The advantage of this model is the ability to predict the onset of the peak of the epidemic, the true number of infected patients at any time point in the process. However, the statistical model turns out to be more consistent with respect to the short-term forecast of the growth rate of infected people and is preferable for calculating the number of infected people only as long as the growth of this value is observed. Conclusion The combined use of the created models for analysis and prediction of the further development of the epidemic allows us to determine the speed and extent of the pandemic defeat throughout the epidemiological process.