A spatial autocorrelation for modelling the spread of coronavirus infections Научная публикация
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SHS Web of Conferences
, E-ISSN: 2261-2424 |
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| Вых. Данные | Год: 2021, Том: 106, Номер статьи : 01001, Страниц : 7 DOI: 10.1051/shsconf/202110601001 | ||||
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Информация о финансировании (1)
| 1 | Российский фонд фундаментальных исследований | 20-04-60188 |
Реферат:
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).
Библиографическая ссылка:
Naumov I.
, Krasnykh S.
, Otmakhova Y.
A spatial autocorrelation for modelling the spread of coronavirus infections
SHS Web of Conferences. 2021. V.106. 01001 :1-7. DOI: 10.1051/shsconf/202110601001 OpenAlex
A spatial autocorrelation for modelling the spread of coronavirus infections
SHS Web of Conferences. 2021. V.106. 01001 :1-7. DOI: 10.1051/shsconf/202110601001 OpenAlex
Идентификаторы БД:
| OpenAlex: | W3162625511 |
Цитирование в БД:
| БД | Цитирований |
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| OpenAlex | 1 |