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?:abstract	Confirmed cases of coronavirus infection, at first approximation, corresponds to models of diffusion of innovations We applied models to analyze spatial patterns in Russia The article describes in detail statistical and other restrictions that reduce the possibility of predicting such phenomena and affect decision-making by the authorities Keeping current trends according to our estimates, as of May 12, the dynamics of confirmed cases will begin to decline in the second half of May, and the end of the active phase of the epidemic, at least in Moscow, can be expected by the end of July The dynamics of confirmed cases are a reduced and delayed reflection of real processes Thus, the introduction of a self-isolation regime in Moscow and many other regions has affected the decrease in the number of new confirmed cases in two weeks In accordance with the model, carriers infected abroad (innovators) were concentrated at the first stage in regions with large agglomerations, in coastal and border regions with a high intensity of internal and external relations Unfortunately, the infection could not be contained;the stage of exponential growth across the country began By mid-April 2020, cases of the disease were recorded in all Russian regions;several cases were in the most remote and least connected regions Among the econometrically identified factors that determine the spread of the disease, one can note a high population density in cities, proximity to the largest metropolitan areas, an increased share of the most active and often traveling part of the population (innovators, migrants), intensive ties within the community and with other countries and regions The spread rate is higher in regions with a high population exposure to diseases, which confirms the theses on the importance of the region s health capital Moreover, the combination of factors and their influence changed in accordance with the stages of diffusion, and at the initial stage, random factors prevailed In conclusion, some directions for further research are given © 2021 Russian Academy of Sciences All rights reserved Confirmed cases of coronavirus infection, at first approximation, corresponds to models of diffusion of innovations We applied models to analyze spatial patterns in Russia The article describes in detail statistical and other restrictions that reduce the possibility of predicting such phenomena and affect decision-making by the authorities Keeping current trends according to our estimates, as of May 12, the dynamics of confirmed cases will begin to decline in the second half of May, and the end of the active phase of the epidemic, at least in Moscow, can be expected by the end of July The dynamics of confirmed cases are a reduced and delayed reflection of real processes Thus, the introduction of a self-isolation regime in Moscow and many other regions� has affected the decrease in the number of new confirmed cases in two weeks In accordance with the model, carriers infected abroad (innovators) were concentrated at the first stage in regions with large agglomerations, in coastal and border regions with a high intensity of internal and external relations Unfortunately, the infection could not be contained;the stage of exponential growth across the country began By mid-April 2020, cases of the disease were recorded in all Russian regions;several cases were in the most remote and least connected regions Among the econometrically identified factors that determine the spread of the disease, one can note a high population density in cities, proximity to the largest metropolitan areas, an increased share of the most active and often traveling part of the population (innovators, migrants), intensive ties within the community and with other countries and regions The spread rate is higher in regions with a high population exposure to diseases, which confirms the theses on the importance of the region’s health capital Moreover, the combination of factors and their influence changed in accordance with the stages of diffusion, and at the initial stage, random factors prevailed In conclusion, some directions for further research are given В регионах России подтвержденная заболеваемость населения коронавирусной инфекцией в первом приближении подчиняется общим пространственным закономерностям диффузии нововведений В статье подробно описаны теоретические подходы к анализу распространения социальных заболеваний и обсуждаются методические ограничения, которые снижают возможности прогнозирования подобных явлений и влияют на принятие решений властями При этом мы считаем, что для большинства регионов, включая Москву, на рассматриваемом периоде до 12 мая 2020 г динамика подтвержденных случаев есть уменьшенное и запаздывающее отражение реальных процессов Исходя из этих предпосылок, введение режима самоизоляции в Москве и ряде других крупных регионов повлияло на снижение числа новых подтвержденных случаев через две недели В соответствии с предложенной моделью носители, заразившиеся за рубежом, на первом этапе концентрировались в регионах с крупными агломерациями, в приморских и приграничных регионах с высокой интенсивностью внутренних и внешних связей К сожалению, заражение не удалось сдержать, начался этап экспоненциального роста по всей стране К началу апреля 2020 г случаи заболевания были зафиксированы в большинстве регионов, кроме наиболее удаленных Согласно расчетам на 12 мая 2020 г , общее число подтвержденных случаев в России может превысить 480 тыс чел К середине мая, по крайней мере, в Москве число новых случаев стало снижаться, что создало предпосылки для снижения ограничений на передвижения жителей В работе показано с помощью эконометрических методов, что для разных периодов диффузии на распространение заболевания влияют различные характеристики регионов Среди них можно отметить высокую плотность населения в городах, близость к крупнейшим агломерациям, повышенную долю наиболее активной и часто путешествующей части населения (новаторов, мигрантов), интенсивные связи внутри сообщества и с другими странами и регионами Скорость распространения выше в регионах с высокой подверженностью населения заболеваниям, что подтверждает тезисы о значимости капитала здоровья региона На начальном этапе случайные факторы преобладали В заключении приведены некоторые направления дальнейших исследований The observed spread of coronavirus infection across Russian regions, as a first approximation, obeys the classic laws of diffusion of innovations The article describes in detail theoretical approaches to the analysis of the spread of social diseases and discusses methodological limitations that reduce the possibility of predicting such phenomena and affect decision-making by the authorities At the same time, we believe that for most regions, including Moscow, until May 12, 2020, the dynamics of confirmed cases are a reduced and delayed reflection of actual processes Thus, the introduced self-isolation regime in Moscow and other agglomerations affected the decrease in the number of newly confirmed cases two weeks after its introduction In accordance with our model, at the first stage, carriers infected abroad were concentrated in regions with large agglomerations and in coastal and border areas with a high intensity of internal and external links Unfortunately, the infection could not be contained, and it started growing exponentially across the country By mid-April 2020, cases of the disease were observed in all Russian regions;however, the remotest regions least connected with other parts of Russia and other countries had only isolated cases By mid-May, at least in Moscow, the number of new cases began to decline, which created the prerequisites for reducing restrictions on the movement of residents However, the decrease in the number of new cases after passing the peak of the epidemic in May is slower than the increase at the beginning These facts contradict the diffusion model;thus, the model is not applicable for epidemiological forecasts based on empirical data Using econometric methods, it is shown that for different periods of diffusion, various characteristics of the regions affect the spread of the disease Among these features we note the high population density in cities, proximity to the largest metropolitan areas, higher proportion of the most active and frequently traveling part of the population (innovators, migrants), and intensive ties within the community, as well as with other regions and countries The virus has spread faster in regions where the population has a higher susceptibility to diseases, which confirms the importance of the region’s health capital The initial stage was dominated by random factors We conclude this paper with directions for further research
?:creator	<https://research.tib.eu/covid-19/entity/Zemtsov%2C_S._P.%3B_Baburin%2C_V._L.>
?:journal	Izvestiya_Rossiiskoi_Akademii_Nauk._Seriya_Geograficheskaya Regional_Research_of_Russia
?:license	unk
?:publication_isRelatedTo_Disease	<https://research.tib.eu/covid-19/entity/COVID-19>
?:source	WHO
?:title	COVID-19: Spatial Dynamics and Diffusion Factors across Russian Regions
?:type	<https://research.tib.eu/covid-19/vocab/Publication>
?:who_covidence_id	#1055432 #859410 #999227
?:year	2020 2021

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?:abstract

Confirmed cases of coronavirus infection, at first approximation, corresponds to models of diffusion of innovations We applied models to analyze spatial patterns in Russia The article describes in detail statistical and other restrictions that reduce the possibility of predicting such phenomena and affect decision-making by the authorities Keeping current trends according to our estimates, as of May 12, the dynamics of confirmed cases will begin to decline in the second half of May, and the end of the active phase of the epidemic, at least in Moscow, can be expected by the end of July The dynamics of confirmed cases are a reduced and delayed reflection of real processes Thus, the introduction of a self-isolation regime in Moscow and many other regions has affected the decrease in the number of new confirmed cases in two weeks In accordance with the model, carriers infected abroad (innovators) were concentrated at the first stage in regions with large agglomerations, in coastal and border regions with a high intensity of internal and external relations Unfortunately, the infection could not be contained;the stage of exponential growth across the country began By mid-April 2020, cases of the disease were recorded in all Russian regions;several cases were in the most remote and least connected regions Among the econometrically identified factors that determine the spread of the disease, one can note a high population density in cities, proximity to the largest metropolitan areas, an increased share of the most active and often traveling part of the population (innovators, migrants), intensive ties within the community and with other countries and regions The spread rate is higher in regions with a high population exposure to diseases, which confirms the theses on the importance of the region s health capital Moreover, the combination of factors and their influence changed in accordance with the stages of diffusion, and at the initial stage, random factors prevailed In conclusion, some directions for further research are given © 2021 Russian Academy of Sciences All rights reserved
Confirmed cases of coronavirus infection, at first approximation, corresponds to models of diffusion of innovations We applied models to analyze spatial patterns in Russia The article describes in detail statistical and other restrictions that reduce the possibility of predicting such phenomena and affect decision-making by the authorities Keeping current trends according to our estimates, as of May 12, the dynamics of confirmed cases will begin to decline in the second half of May, and the end of the active phase of the epidemic, at least in Moscow, can be expected by the end of July The dynamics of confirmed cases are a reduced and delayed reflection of real processes Thus, the introduction of a self-isolation regime in Moscow and many other regions� has affected the decrease in the number of new confirmed cases in two weeks In accordance with the model, carriers infected abroad (innovators) were concentrated at the first stage in regions with large agglomerations, in coastal and border regions with a high intensity of internal and external relations Unfortunately, the infection could not be contained;the stage of exponential growth across the country began By mid-April 2020, cases of the disease were recorded in all Russian regions;several cases were in the most remote and least connected regions Among the econometrically identified factors that determine the spread of the disease, one can note a high population density in cities, proximity to the largest metropolitan areas, an increased share of the most active and often traveling part of the population (innovators, migrants), intensive ties within the community and with other countries and regions The spread rate is higher in regions with a high population exposure to diseases, which confirms the theses on the importance of the region’s health capital Moreover, the combination of factors and their influence changed in accordance with the stages of diffusion, and at the initial stage, random factors prevailed In conclusion, some directions for further research are given В регионах России подтвержденная заболеваемость населения коронавирусной инфекцией в первом приближении подчиняется общим пространственным закономерностям диффузии нововведений В статье подробно описаны теоретические подходы к анализу распространения социальных заболеваний и обсуждаются методические ограничения, которые снижают возможности прогнозирования подобных явлений и влияют на принятие решений властями При этом мы считаем, что для большинства регионов, включая Москву, на рассматриваемом периоде до 12 мая 2020 г динамика подтвержденных случаев есть уменьшенное и запаздывающее отражение реальных процессов Исходя из этих предпосылок, введение режима самоизоляции в Москве и ряде других крупных регионов повлияло на снижение числа новых подтвержденных случаев через две недели В соответствии с предложенной моделью носители, заразившиеся за рубежом, на первом этапе концентрировались в регионах с крупными агломерациями, в приморских и приграничных регионах с высокой интенсивностью внутренних и внешних связей К сожалению, заражение не удалось сдержать, начался этап экспоненциального роста по всей стране К началу апреля 2020 г случаи заболевания были зафиксированы в большинстве регионов, кроме наиболее удаленных Согласно расчетам на 12 мая 2020 г , общее число подтвержденных случаев в России может превысить 480 тыс чел К середине мая, по крайней мере, в Москве число новых случаев стало снижаться, что создало предпосылки для снижения ограничений на передвижения жителей В работе показано с помощью эконометрических методов, что для разных периодов диффузии на распространение заболевания влияют различные характеристики регионов Среди них можно отметить высокую плотность населения в городах, близость к крупнейшим агломерациям, повышенную долю наиболее активной и часто путешествующей части населения (новаторов, мигрантов), интенсивные связи внутри сообщества и с другими странами и регионами Скорость распространения выше в регионах с высокой подверженностью населения заболеваниям, что подтверждает тезисы о значимости капитала здоровья региона На начальном этапе случайные факторы преобладали В заключении приведены некоторые направления дальнейших исследований
The observed spread of coronavirus infection across Russian regions, as a first approximation, obeys the classic laws of diffusion of innovations The article describes in detail theoretical approaches to the analysis of the spread of social diseases and discusses methodological limitations that reduce the possibility of predicting such phenomena and affect decision-making by the authorities At the same time, we believe that for most regions, including Moscow, until May 12, 2020, the dynamics of confirmed cases are a reduced and delayed reflection of actual processes Thus, the introduced self-isolation regime in Moscow and other agglomerations affected the decrease in the number of newly confirmed cases two weeks after its introduction In accordance with our model, at the first stage, carriers infected abroad were concentrated in regions with large agglomerations and in coastal and border areas with a high intensity of internal and external links Unfortunately, the infection could not be contained, and it started growing exponentially across the country By mid-April 2020, cases of the disease were observed in all Russian regions;however, the remotest regions least connected with other parts of Russia and other countries had only isolated cases By mid-May, at least in Moscow, the number of new cases began to decline, which created the prerequisites for reducing restrictions on the movement of residents However, the decrease in the number of new cases after passing the peak of the epidemic in May is slower than the increase at the beginning These facts contradict the diffusion model;thus, the model is not applicable for epidemiological forecasts based on empirical data Using econometric methods, it is shown that for different periods of diffusion, various characteristics of the regions affect the spread of the disease Among these features we note the high population density in cities, proximity to the largest metropolitan areas, higher proportion of the most active and frequently traveling part of the population (innovators, migrants), and intensive ties within the community, as well as with other regions and countries The virus has spread faster in regions where the population has a higher susceptibility to diseases, which confirms the importance of the region’s health capital The initial stage was dominated by random factors We conclude this paper with directions for further research

?:creator