Algorithm and Results of Short-Term Forecast of Changes in the COVID-19 Spread Coefficient in the Constituent Entities of the Russian Federation

ABSTRACT

There was a decrease in the number of COVID-19 cases across many entities of the Russian Federation towards the end of summer season-2020. However, the disease remains a relevant threat to the public health and economy and the possibility of a second epidemic wave is not excluded. Rate of infection transmission (Rt) is one of the most important indicators to justify the transition to next stage of removing/introducing restrictive measures on COVID-19. Objective of the work was to describe the algorithm of analysis and short-term forecast of coronavirus spread rate, to assess correspondence between theoretically expected and actual values of this indicator. Materials and methods. Procedure for making a short-term extrapolation forecast of Rt in 10 RF constituent entities, depending on the presence or absence of indicator trends with calculation of a 95 % confidence interval of possible changes in its value is provided. Results and discussion. It is proposed to carry out Rt forecast based on averaged values over a week, combining regression analysis and expert assessment of time series dynamics nature for prompt transition from trend forecasting to extrapolation of stationary observation sequences and vice versa. It has been demonstrated that predicted Rt values are not statistically different from actual values. When making managerial decisions on COVID-19 prevention, special attention should be paid to cases when actual value of Rt exceeds the upper limit of confidence interval. Six (20.0 %) such cases were detected in surveyed entities on calendar weeks 33-35. Three of them were registered in Trans-Baikal Territory, where upward trend was reported during that period of time. The cause of this phenomenon should be analyzed. The put forward algorithm of analysis and forecasting of the Rt value changes, which was tested in 10 entities of Russia, provides a reliable basis for making management decisions on removing/introducing restrictive measures for COVID-19 prevention. © 2021 Russian Research Anti-Plague Institute. All rights reserved.