| Issue |
SHS Web Conf.
Volume 106, 2021
III International Scientific and Practical Conference “Modern Management Trends and the Digital Economy: from Regional Development to Global Economic Growth” (MTDE 2021)
|
|
|---|---|---|
| Article Number | 01001 | |
| Number of page(s) | 7 | |
| Section | Digital Technologies in Socio-Economic Systems Management | |
| DOI | https://doi.org/10.1051/shsconf/202110601001 | |
| Published online | 18 May 2021 | |
A spatial autocorrelation for modelling the spread of coronavirus infections
1
Institute of Economics of the Ural Branch of the Russian Academy of Sciences, Ekaterinburg, Russia
2
Central Economics and Mathematics Institute of the Russian Academy of Sciences, Moscow, Russia
* Corresponding author: krasnykh.ss@uiec.ru
Spatial autocorrelation methods are used to study spatial disproportions in the socio-economic development of territories. The most common research methods are the analysis of Moran local indices, Moran global index, Getis-Ord hot spots. In this study, we used spatial autocorrelation methods to estimate COVID-19 distribution patterns. As a result of the study, we identified the formed growth poles, the epicenters of the spread of infection (St. Petersburg, Sverdlovsk and Nizhny Novgorod regions) and only emerging ones. The practical application of this methodological approach allowed us to predict further spatial directions of the spread of coronavirus infection (Vladimir, Kaluga, Smolensk, Tula, Tver, Yaroslavl, Ryazan and Leningrad regions).
© The Authors, published by EDP Sciences, 2021
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