5 research outputs found
ΠΠ΅ΡΠΎΠ΄ΠΈΠΊΠ° ΠΎΡΠ΅Π½ΠΊΠΈ ΠΎΠΆΠΈΠ΄Π°Π΅ΠΌΠΎΠΉ ΡΡΠΎΠΈΠΌΠΎΡΡΠΈ ΠΏΡΠΎΠ΅ΠΊΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠ΅Ρ Π½ΠΈΡΠ΅ΡΠΊΠΈΡ ΠΈ ΡΠ΅Ρ Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ ΠΈΠ½Π½ΠΎΠ²Π°ΡΠΈΠΉ
The article proposes a methodology for estimating the expected cost of technical and technological innovations. The evaluation is performed in the pre-design phase of the innovation (project initiation phase). It relies on the method of analogy and is implemented based on the principle of βso was - so will be.β At the same time, the available analogues provide objective information about βhow it was.β Extending this data into the future to estimate the cost of design relies on probabilistic interpretation of the available uncertainty. Uncertainty removal is accomplished using the principle of maximum entropy. This ensures the most complete consideration of the available objective information and minimizes speculation in assessing the cost of designing innovative objects. In general, the methodology proposed in the article allows obtaining objective estimates of the expected cost of designing technical and technological innovations in the standard information situation for the initiation stage of the project.Π ΡΡΠ°ΡΡΠ΅ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π° ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠ° ΠΎΡΠ΅Π½ΠΊΠΈ ΠΎΠΆΠΈΠ΄Π°Π΅ΠΌΠΎΠΉ ΡΡΠΎΠΈΠΌΠΎΡΡΠΈ ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈΠ½Π½ΠΎΠ²Π°ΡΠΈΠΉ. ΠΡΠ΅Π½ΠΊΠ° ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΠ΅ΡΡΡ Π½Π° ΡΡΠ°ΠΏΠ΅, ΠΏΡΠ΅Π΄ΡΠ΅ΡΡΠ²ΡΡΡΠ΅ΠΌ ΠΏΡΠΎΠ΅ΠΊΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈΠ½Π½ΠΎΠ²Π°ΡΠΈΠΉ (ΡΡΠ°ΠΏΠ΅ ΠΈΠ½ΠΈΡΠΈΠ°ΡΠΈΠΈ ΠΏΡΠΎΠ΅ΠΊΡΠ°). ΠΠ½Π° ΠΎΠΏΠΈΡΠ°Π΅ΡΡΡ Π½Π° ΠΌΠ΅ΡΠΎΠ΄ Π°Π½Π°Π»ΠΎΠ³ΠΈΠΉ ΠΈ ΡΠ΅Π°Π»ΠΈΠ·ΡΠ΅ΡΡΡ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΏΡΠΈΠ½ΡΠΈΠΏΠ° Β«ΡΠ°ΠΊ Π±ΡΠ»ΠΎ - ΡΠ°ΠΊ Π±ΡΠ΄Π΅ΡΒ». ΠΡΠΈ ΡΡΠΎΠΌ ΠΈΠΌΠ΅ΡΡΠΈΠ΅ΡΡ Π°Π½Π°Π»ΠΎΠ³ΠΈ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΠ²Π°ΡΡ ΠΎΠ±ΡΠ΅ΠΊΡΠΈΠ²Π½ΡΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ ΠΎ ΡΠΎΠΌ Β«ΠΊΠ°ΠΊ Π±ΡΠ»ΠΎΒ». ΠΡΠΎΠ»ΠΎΠ½Π³Π°ΡΠΈΡ ΡΡΠΈΡ
Π΄Π°Π½Π½ΡΡ
Π² Π±ΡΠ΄ΡΡΠ΅Π΅ Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΡΡΠΎΠΈΠΌΠΎΡΡΠΈ ΠΏΡΠΎΠ΅ΠΊΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΎΠΏΠΈΡΠ°Π΅ΡΡΡ Π½Π° Π²Π΅ΡΠΎΡΡΠ½ΠΎΡΡΠ½ΡΡ ΠΈΠ½ΡΠ΅ΡΠΏΡΠ΅ΡΠ°ΡΠΈΡ ΠΈΠΌΠ΅ΡΡΠ΅ΠΉΡΡ Π½Π΅ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΠΎΡΡΠΈ. Π‘Π½ΡΡΠΈΠ΅ Π½Π΅ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΠΎΡΡΠΈ ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΠ΅ΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΏΡΠΈΠ½ΡΠΈΠΏΠ° ΠΌΠ°ΠΊΡΠΈΠΌΡΠΌΠ° ΡΠ½ΡΡΠΎΠΏΠΈΠΈ. ΠΡΠΎ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΠ²Π°Π΅Ρ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΠΏΠΎΠ»Π½ΡΠΉ ΡΡΠ΅Ρ ΠΈΠΌΠ΅ΡΡΠ΅ΠΉΡΡ ΠΎΠ±ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΈ ΠΌΠΈΠ½ΠΈΠΌΠΈΠ·ΠΈΡΡΠ΅Ρ Π΄ΠΎΠΌΡΡΠ»Ρ ΠΏΡΠΈ ΠΎΡΠ΅Π½ΠΊΠ΅ ΡΡΠΎΠΈΠΌΠΎΡΡΠΈ ΠΏΡΠΎΠ΅ΠΊΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈΠ½Π½ΠΎΠ²Π°ΡΠΈΠΎΠ½Π½ΡΡ
ΠΎΠ±ΡΠ΅ΠΊΡΠΎΠ². Π ΡΠ΅Π»ΠΎΠΌ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½Π°Ρ Π² ΡΡΠ°ΡΡΠ΅ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠ° ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ Π² ΡΠΈΠΏΠΎΠ²ΠΎΠΉ Π΄Π»Ρ ΡΡΠ°ΠΏΠ° ΠΈΠ½ΠΈΡΠΈΠ°ΡΠΈΠΈ ΠΏΡΠΎΠ΅ΠΊΡΠ° ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΡΠΈΡΡΠ°ΡΠΈΠΈ ΠΏΠΎΠ»ΡΡΠ°ΡΡ ΠΎΠ±ΡΠ΅ΠΊΡΠΈΠ²Π½ΡΠ΅ ΠΎΡΠ΅Π½ΠΊΠΈ ΠΎΠΆΠΈΠ΄Π°Π΅ΠΌΠΎΠΉ ΡΡΠΎΠΈΠΌΠΎΡΡΠΈ ΠΏΡΠΎΠ΅ΠΊΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈΠ½Π½ΠΎΠ²Π°ΡΠΈΠΉ
ΠΠΎΠ΄Π΅Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄ ΠΊΠ°Π»Π΅Π½Π΄Π°ΡΠ½ΠΎΠ³ΠΎ ΠΏΠ»Π°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π»ΠΎΠ³ΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² ΠΏΠ΅ΡΠ΅ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡΠΈΡ ΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΠΉ Π°Π³ΡΠΎΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΠ³ΠΎ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ°
A model and method for the formation of optimal calendar plans for the organization of logisticsΒ processes for the functioning of enterprises of the agro-industrial complex have been developed.Β The model is based on the presentation of the procedure for the formation of an optimal calendarΒ plan in the form of a discrete programming problem. The optimization method is based on theΒ procedure of branches and boundaries. The proposed model and method are the basis for creatingΒ specific methods for the formation of optimal calendar plans for the organization of logisticalΒ processes of the functioning of the agro industrial complex.Π Π°Π·ΡΠ°Π±ΠΎΡΠ°Π½Ρ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΡ
ΠΊΠ°Π»Π΅Π½Π΄Π°ΡΠ½ΡΡ
ΠΏΠ»Π°Π½ΠΎΠ² ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΠΈΒ Π»ΠΎΠ³ΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΠ΅ΡΠ΅ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡΠΈΡ
ΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΠΉ Π°Π³ΡΠΎΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΠ³ΠΎ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ° (ΠΠΠ). ΠΠΎΠ΄Π΅Π»Ρ ΠΎΡΠ½ΠΎΠ²Π°Π½Π° Π½Π° ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ΠΈΠΈ ΠΏΡΠΎΡΠ΅Π΄ΡΡΡ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡΒ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΊΠ°Π»Π΅Π½Π΄Π°ΡΠ½ΠΎΠ³ΠΎ ΠΏΠ»Π°Π½Π° Π² Π²ΠΈΠ΄Π΅ Π·Π°Π΄Π°ΡΠΈ Π΄ΠΈΡΠΊΡΠ΅ΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ. Π ΠΎΡΠ½ΠΎΠ²Ρ ΠΌΠ΅ΡΠΎΠ΄Π° ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½Π° ΠΏΡΠΎΡΠ΅Π΄ΡΡΠ° Π²Π΅ΡΠ²Π΅ΠΉ ΠΈ Π³ΡΠ°Π½ΠΈΡ. ΠΡΠ΅Π΄Π»Π°Π³Π°Π΅ΠΌΡΠ΅ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄ ΡΠ²Π»ΡΡΡΡΡ Π±Π°Π·ΠΎΠΉ Π΄Π»Ρ ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΡΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΡ
ΠΊΠ°Π»Π΅Π½Π΄Π°ΡΠ½ΡΡ
ΠΏΠ»Π°Π½ΠΎΠ² ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΠΈ Π»ΠΎΠ³ΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΠΉ ΠΠΠ
METHODOLOGICAL APPROACH TO ASSESSING THE EFFICIENCY OF CUSTOMS RISK MANAGEMENT
The article proposes a model for assessing the efficiency of the functioning of the customs risk management system. The model is based on the theoretical and probabilistic representation of the process of possible violation of customs legislation by participants in foreign economic activity. The peculiarity of the model consists in the complex accounting of the direct and latent effects of the functioning of the customs risk management system. The initial information of the model is made up of statistical data on the results of its functioning
Π₯Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΈΡΡΠ°ΡΠΈΠΈ ΠΏΠΎ COVID-19 Π² Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ Π² 2020 Π³.
Background.The COVID-19 epidemic in the Russian Federation, which began in March 2020, caused serious damage to health of the population and led to severe economic losses. By December 28, 2020, 3 078 035 cases of COVID-19 and 55 265 lethal outcomes were registered in the country. The population of all territorial subjects of the country is involved in the epidemic process of COVID-19. The severe epidemiological situation made it necessary to conduct an analysis to identify the factors that determine the high intensity of the epidemic process, as well as the population groups with the highest risk of SARS-CoV-2 infection.
Aims to study the patterns of SARS-CoV-2 spread and the epidemiological features of the initial stage of the COVID-19 pandemic in the Russian Federation in 2020.
Methods.An epidemiological analysis of the COVID-19 situation in the Russian Federation was carried out to determine the dynamics of morbidity, the gender proportion and age structure of patients, the proportion of hospitalized patients, the ratio of various forms of infection, the social and professional status of patients. Standard methods of descriptive statistics Microsoft Excel and STATISTICA 12.0 (StatSoft, USA) were used for statistical processing. The mean values were estimated with a 95% confidence interval [95% CI] (the exact Klopper Pearson method).
Results.During the observation time (2020), several periods were identified in the dynamics of the new COVID-19 cases detection: the period of importation of SARS-CoV-2 and the increase in morbidity, the period of epidemic decline, the period of autumn growth, the period of sustained high incidence of COVID-19. It was found that people over 70 years of age are the group with the highest risk of infection and a more severe course of COVID-19. The presence of target contingents among social and professional groups of the population, which should include medical workers, retired person, employees of educational institutions, law enforcement agencies, transport, who require special attention and medical and social support, was shown.
Conclusions.The analysis showed that the large-scale spread of COVID-19 requires in-depth epidemiological studies and the development of additional disease control measures, taking into account the dynamics of the incidence of this socially significant infection.ΠΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠ΅.ΠΠΏΠΈΠ΄Π΅ΠΌΠΈΡCOVID-19Π²Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ, Π½Π°ΡΠ°Π²ΡΠΈΡΡΠ²ΠΌΠ°ΡΡΠ΅ 2020 Π³., Π½Π°Π½Π΅ΡΠ»Π° ΡΠ΅ΡΡΠ΅Π·Π½Π΅ΠΉΡΠΈΠΉ ΡΡΠ΅ΡΠ± Π·Π΄ΠΎΡΠΎΠ²ΡΡ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡΠΈΠΏΡΠΈΠ²Π΅Π»Π°ΠΊΡΡΠΆΠ΅Π»ΡΠΌ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΏΠΎΡΠ΅ΡΡΠΌ.Π28 Π΄Π΅ΠΊΠ°Π±ΡΡ 2020 Π³.Π²ΡΡΡΠ°Π½Π΅ Π·Π°ΡΠ΅Π³ΠΈΡΡΡΠΈΡΠΎΠ²Π°Π½ΠΎ 3 078 035 ΡΠ»ΡΡΠ°ΡCOVID-19ΠΈ55 265 Π»Π΅ΡΠ°Π»ΡΠ½ΡΡ
ΠΈΡΡ
ΠΎΠ΄ΠΎΠ².ΠΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΏΡΠΎΡΠ΅ΡΡCOVID-19 Π²ΠΎΠ²Π»Π΅ΡΠ΅Π½ΠΎ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΠ΅ Π²ΡΠ΅Ρ
ΡΡΠ±ΡΠ΅ΠΊΡΠΎΠ² Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ. Π’ΡΠΆΠ΅Π»Π°Ρ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠ°Ρ ΡΠΈΡΡΠ°ΡΠΈΡΠ²ΡΡΡΠ°Π½Π΅ ΠΎΠ±ΡΡΠ»ΠΎΠ²ΠΈΠ»Π° Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΡΡΡ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ Π°Π½Π°Π»ΠΈΠ·Π°ΡΠ²ΡΡΠ²Π»Π΅Π½ΠΈΠ΅ΠΌ ΡΠ°ΠΊΡΠΎΡΠΎΠ², ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΡΡΠΈΡ
Π²ΡΡΠΎΠΊΡΡ ΠΈΠ½ΡΠ΅Π½ΡΠΈΠ²Π½ΠΎΡΡΡ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡΠ°,Π°ΡΠ°ΠΊΠΆΠ΅ Π³ΡΡΠΏΠΏ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡΡΠ½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π²ΡΡΠΎΠΊΠΈΠΌ ΡΠΈΡΠΊΠΎΠΌ ΠΈΠ½ΡΠΈΡΠΈΡΠΎΠ²Π°Π½ΠΈΡSARS-CoV-2.
Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΈΠ·ΡΡΠΈΡΡ Π·Π°ΠΊΠΎΠ½ΠΎΠΌΠ΅ΡΠ½ΠΎΡΡΠΈ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡSARS-CoV-2ΠΈΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ Π½Π°ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΡΠ°ΠΏΠ° ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈCOVID-19Π²Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈΠ²2020 Π³.
ΠΠ΅ΡΠΎΠ΄Ρ.ΠΡΠΎΠ²Π΅Π΄Π΅Π½ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°Π½Π°Π»ΠΈΠ· ΡΠΈΡΡΠ°ΡΠΈΠΈΠΏΠΎCOVID-19Π²Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈΡΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ΠΌ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈ, Π³Π΅Π½Π΄Π΅ΡΠ½ΠΎΠΉ ΠΏΡΠΎΠΏΠΎΡΡΠΈΠΈΠΈΠ²ΠΎΠ·ΡΠ°ΡΡΠ½ΠΎΠΉ ΡΡΡΡΠΊΡΡΡΡ Π·Π°Π±ΠΎΠ»Π΅Π²ΡΠΈΡ
, ΡΠ΄Π΅Π»ΡΠ½ΠΎΠ³ΠΎ Π²Π΅ΡΠ° Π³ΠΎΡΠΏΠΈΡΠ°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ², ΡΠΎΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΡΠΎΡΠΌ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ, ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎΠ³ΠΎΠΈΠΏΡΠΎΡΠ΅ΡΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΡΠ°ΡΡΡΠ° Π·Π°Π±ΠΎΠ»Π΅Π²ΡΠΈΡ
.ΠΠ»ΡΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ ΡΡΠ°Π½Π΄Π°ΡΡΠ½ΡΠ΅ ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΎΠΏΠΈΡΠ°ΡΠ΅Π»ΡΠ½ΠΎΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ Microsoft ExcelΠΈSTATISTICA 12.0 (StatSoft, Π‘Π¨Π). Π‘ΡΠ΅Π΄Π½ΠΈΠ΅ Π·Π½Π°ΡΠ΅Π½ΠΈΡ ΠΎΡΠ΅Π½ΠΈΠ²Π°Π»ΠΈΡΡΡΠ΅ΡΠΎΠΌ 95% Π΄ΠΎΠ²Π΅ΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΠΈΠ½ΡΠ΅ΡΠ²Π°Π»Π° [95% ΠΠ] (ΠΏΠΎ ΡΠΎΡΠ½ΠΎΠΌΡ ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΠ»ΠΎΠΏΠΏΠ΅ΡΠ°ΠΠΈΡΡΠΎΠ½Π°).
Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ.ΠΠ°Π²ΡΠ΅ΠΌΡ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΡ (2020 Π³.) Π²ΡΠ΄Π΅Π»Π΅Π½ΠΎ Π½Π΅ΡΠΊΠΎΠ»ΡΠΊΠΎ ΠΏΠ΅ΡΠΈΠΎΠ΄ΠΎΠ²Π²Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ΅ Π²ΡΡΠ²Π»Π΅Π½ΠΈΡ Π½ΠΎΠ²ΡΡ
ΡΠ»ΡΡΠ°Π΅Π²COVID-19: ΠΏΠ΅ΡΠΈΠΎΠ΄ Π·Π°Π²ΠΎΠ·Π°SARS-CoV-2ΠΈΡΠΎΡΡΠ° Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈ, ΠΏΠ΅ΡΠΈΠΎΠ΄ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π·Π°ΡΠΈΡΡΡ, ΠΏΠ΅ΡΠΈΠΎΠ΄ ΠΎΡΠ΅Π½Π½Π΅Π³ΠΎ ΠΏΠΎΠ΄ΡΠ΅ΠΌΠ°, ΠΏΠ΅ΡΠΈΠΎΠ΄ ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎ Π²ΡΡΠΎΠΊΠΎΠ³ΠΎ ΡΡΠΎΠ²Π½Ρ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈCOVID-19. Π£ΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΎ,ΡΡΠΎΠ»ΠΈΡΠ° ΡΡΠ°ΡΡΠ΅ 70 Π»Π΅Ρ ΡΠ²Π»ΡΡΡΡΡ Π³ΡΡΠΏΠΏΠΎΠΉΡΠ½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π²ΡΡΠΎΠΊΠΈΠΌ ΡΠΈΡΠΊΠΎΠΌ Π·Π°ΡΠ°ΠΆΠ΅Π½ΠΈΡΠΈΠ±ΠΎΠ»Π΅Π΅ ΡΡΠΆΠ΅Π»ΡΠΌ ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ΠΌCOVID-19. ΠΠΎΠΊΠ°Π·Π°Π½ΠΎ Π½Π°Π»ΠΈΡΠΈΠ΅ ΡΠ΅Π»Π΅Π²ΡΡ
ΠΊΠΎΠ½ΡΠΈΠ½Π³Π΅Π½ΡΠΎΠ² ΡΡΠ΅Π΄ΠΈ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΡΡ
ΠΈΠΏΡΠΎΡΠ΅ΡΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Π³ΡΡΠΏΠΏ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ,ΠΊΡΠΈΡΠ»Ρ ΠΊΠΎΡΠΎΡΡΡ
ΡΠ»Π΅Π΄ΡΠ΅Ρ ΠΎΡΠ½Π΅ΡΡΠΈ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΈΡ
ΡΠ°Π±ΠΎΡΠ½ΠΈΠΊΠΎΠ², ΠΏΠ΅Π½ΡΠΈΠΎΠ½Π΅ΡΠΎΠ², ΡΠ°Π±ΠΎΡΠ½ΠΈΠΊΠΎΠ² ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°ΡΠ΅Π»ΡΠ½ΡΡ
ΡΡΡΠ΅ΠΆΠ΄Π΅Π½ΠΈΠΉ, ΠΏΡΠ°Π²ΠΎΠΎΡ
ΡΠ°Π½ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΎΡΠ³Π°Π½ΠΎΠ², ΡΡΠ°Π½ΡΠΏΠΎΡΡΠ°, ΠΊΠΎΡΠΎΡΡΠ΅ ΡΡΠ΅Π±ΡΡΡ ΠΎΡΠΎΠ±ΠΎΠ³ΠΎ Π²Π½ΠΈΠΌΠ°Π½ΠΈΡΠΈΠΌΠ΅Π΄ΠΈΠΊΠΎ-ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎΠΉ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠΈ.
ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅.ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΠΏΠΎΠΊΠ°Π·Π°Π»,ΡΡΠΎΠΌΠ°ΡΡΡΠ°Π±Π½ΠΎΠ΅ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΠ΅ COVID-19 ΡΡΠ΅Π±ΡΠ΅Ρ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΡΠ³Π»ΡΠ±Π»Π΅Π½Π½ΡΡ
ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉΠΈΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΏΡΠΎΡΠΈΠ²ΠΎΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ΅ΡΠΎΠΏΡΠΈΡΡΠΈΠΉΡΡΡΠ΅ΡΠΎΠΌ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈ ΡΡΠΎΠΉ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ Π·Π½Π°ΡΠΈΠΌΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠ΅ΠΉ