Spatial patterns of COVID-19 distribution in Russia and the world: cartographic analysis

The article is devoted to the analysis of spatial patterns of COVID-19 distribution, the geography of which was fully manifested in the period from February to May 2020. It is during this period that clear areas and boundaries of regional differences of «spreading» are recorded, associated with existing logistical, socio-economic and center-peripheral factors. Later monitoring of COVID-19 shows an averaging of indicators (at dawn per 100 thousand inhabitants) and a kind of leveling of the epidemiological situation in accordance with the population density.

The paper uses data on morbidity in conjunction with management measures, which in turn were dictated not only by the objective epidemiological situation, but also by regional features of socio-political processes. We use Yandex data on self-isolation and our own media monitoring of conflicts and hotbeds of social tension (increased fears) in Russia. The COVID-19 geo-information system is used by ArcGIS for analysis and mapping.

Spatial analysis is built in the logic of multi-scale, i.e. World, Russia, Moscow. All three levels are characterized by a «diffusion of coronavirus innovations» associated with the beginning of spread in well-off and socially-economically developed urban centers. Then the center of distribution shifts to peripheral less developed territories. For Russia, at the initial stages of COVID-19 distribution, there are three main centers, namely Moscow and the Moscow region, oil and gas-bearing regions and the North, and the North Caucasus. The main factors of the high rate of virus spread in these territories are both the developed transport and logistics characteristics, and a set of unique regional features, such as increased contact and a weak health system in Dagestan, shift flows and crowding of shift settlements in the Yamal-Nenets Autonomous district, and a high share of the creative class in the Moscow region.

The work is a monitoring study and will be supplemented with new data, maps and analytics. By the end of 2020 – beginning of 2021, it will be possible to assess the contribution of COVID-19 to overall mortality and analyze in detail the demographic consequences of the spread of the virus.

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